Hadoop HDFS
  1. Hadoop HDFS
  2. HDFS-4949

Centralized cache management in HDFS

    Details

    • Type: New Feature New Feature
    • Status: Closed
    • Priority: Major Major
    • Resolution: Fixed
    • Affects Version/s: 3.0.0, 2.3.0
    • Fix Version/s: 2.3.0
    • Component/s: datanode, namenode
    • Labels:
      None

      Description

      HDFS currently has no support for managing or exposing in-memory caches at datanodes. This makes it harder for higher level application frameworks like Hive, Pig, and Impala to effectively use cluster memory, because they cannot explicitly cache important datasets or place their tasks for memory locality.

      1. HDFS-4949-consolidated.patch
        503 kB
        Andrew Wang
      2. hdfs-4949-branch-2.patch
        698 kB
        Andrew Wang
      3. caching-testplan.pdf
        99 kB
        Stephen Chu
      4. caching-design-doc-2013-10-24.pdf
        312 kB
        Colin Patrick McCabe
      5. caching-design-doc-2013-08-09.pdf
        305 kB
        Andrew Wang
      6. caching-design-doc-2013-07-02.pdf
        270 kB
        Andrew Wang

        Issue Links

        1.
        Add JNI mlock support Sub-task Resolved Andrew Wang
         
        2.
        Propagate cache status information from the DataNode to the NameNode Sub-task Resolved Andrew Wang
         
        3.
        Add DataNode support for mlock and munlock Sub-task Resolved Andrew Wang
         
        4.
        Add cacheRequest/uncacheRequest support to NameNode Sub-task Resolved Colin Patrick McCabe
         
        5.
        NameNode should invoke DataNode APIs to coordinate caching Sub-task Resolved Andrew Wang
         
        6.
        add RPCs for creating and manipulating cache pools Sub-task Resolved Colin Patrick McCabe
         
        7.
        add command-line support for manipulating cache pools Sub-task Resolved Colin Patrick McCabe
         
        8.
        Add cache status information to datanode heartbeat Sub-task Resolved Andrew Wang
         
        9.
        add command-line support for manipulating cache directives Sub-task Resolved Colin Patrick McCabe
         
        10.
        miscellaneous cache pool RPC fixes Sub-task Resolved Colin Patrick McCabe
         
        11.
        prettier dfsadmin -listCachePools output Sub-task Resolved Colin Patrick McCabe
         
        12.
        revisit zero-copy API in FSDataInputStream to make it more intuitive Sub-task Resolved Colin Patrick McCabe
         
        13.
        Automatically cache new data added to a cached path Sub-task Resolved Colin Patrick McCabe
         
        14.
        Persist CacheManager state in the edit log Sub-task Resolved Andrew Wang
         
        15.
        Support for federated cache pools Sub-task Resolved Andrew Wang
         
        16.
        caching PB cleanups Sub-task Resolved Colin Patrick McCabe
         
        17.
        Move cache pool related CLI commands to CacheAdmin Sub-task Resolved Andrew Wang
         
        18.
        NameNodeRpcServer must not send back DNA_FINALIZE in reply to a cache report Sub-task Resolved Colin Patrick McCabe
         
        19.
        NativeIO: consolidate getrlimit into NativeIO#getMemlockLimit Sub-task Resolved Colin Patrick McCabe
         
        20.
        Fix some failing unit tests on HDFS-4949 branch Sub-task Resolved Andrew Wang
         
        21.
        separate PathBasedCacheEntry and PathBasedCacheDirectiveWithId Sub-task Resolved Colin Patrick McCabe
         
        22.
        Refactor PathBasedCache* methods to use a Path rather than a String Sub-task Resolved Chris Nauroth
         
        23.
        Change PathBasedCacheDirective APIs to be a single value rather than batch Sub-task Resolved Andrew Wang
         
        24.
        Add requesting user's name to PathBasedCacheEntry Sub-task Resolved Andrew Wang
         
        25.
        Expose if a block replica is cached in getFileBlockLocations Sub-task Resolved Andrew Wang
         
        26.
        Fix failing caching unit tests Sub-task Resolved Andrew Wang
         
        27.
        Do not expose CachePool type in AddCachePoolOp Sub-task Resolved Colin Patrick McCabe
         
        28.
        Add datanode caching metrics Sub-task Closed Andrew Wang
         
        29.
        add modifyDirective to cacheAdmin Sub-task Resolved Colin Patrick McCabe
         
        30.
        Fix error message when dfs.datanode.max.locked.memory is improperly configured Sub-task Resolved Colin Patrick McCabe
         
        31.
        DNA_CACHE and DNA_UNCACHE should be by blockId only Sub-task Resolved Colin Patrick McCabe
         
        32.
        Add replication field to PathBasedCacheDirective Sub-task Resolved Colin Patrick McCabe
         
        33.
        Allow LightWeightGSet#Iterator to remove elements Sub-task Resolved Colin Patrick McCabe
         
        34.
        recaching improvements Sub-task Closed Colin Patrick McCabe
         
        35.
        In CacheReport, don't send genstamp and length on the wire Sub-task Resolved Colin Patrick McCabe
         
        36.
        fix broken caching unit tests Sub-task Resolved Andrew Wang
         
        37.
        Loading fsimage fails to find cache pools during namenode startup. Sub-task Resolved Chris Nauroth
         
        38.
        Concurrent clients that add a cache directive on the same path may prematurely uncache from each other. Sub-task Resolved Chris Nauroth
         
        39.
        fix race conditions in DN caching and uncaching Sub-task Closed Colin Patrick McCabe
         
        40.
        Add feature documentation for datanode caching. Sub-task Closed Colin Patrick McCabe
         
        41.
        Caching RPCs are AtMostOnce, but do not persist client ID and call ID to edit log. Sub-task Resolved Chris Nauroth
         
        42.
        Resolve regressions in Windows compatibility on HDFS-4949 branch. Sub-task Resolved Chris Nauroth
         
        43.
        Fix possible RetryCache hang for caching RPC handlers in FSNamesystem Sub-task Resolved Andrew Wang
         
        44.
        Fixup test-patch.sh warnings on HDFS-4949 branch Sub-task Resolved Andrew Wang
         
        45.
        Support TTL on CacheDirectives Sub-task Closed Andrew Wang
         
        46.
        support cachepool-based limit management in path-based caching Sub-task Closed Andrew Wang
         
        47.
        better API for getting the cached blocks locations Sub-task Closed Andrew Wang
         
        48.
        Add byte and file statistics to PathBasedCacheEntry Sub-task Closed Colin Patrick McCabe
         
        49.
        Consistent naming of user-visible caching classes and methods Sub-task Closed Colin Patrick McCabe
         
        50.
        add command-line support for modifyDirective Sub-task Resolved Colin Patrick McCabe
         
        51.
        Consider maximum DN memory, stale status when scheduling recaching Sub-task Resolved Colin Patrick McCabe
         
        52.
        TestPathBasedCacheRequests#testReplicationFactor is flaky Sub-task Closed Andrew Wang
         
        53.
        improve CacheManipulator interface to allow better unit testing Sub-task Closed Colin Patrick McCabe
         
        54.
        loading cache path directives from edit log doesn't update nextEntryId Sub-task Closed Colin Patrick McCabe
         
        55.
        skip checksums when reading a cached block via non-local reads Sub-task Resolved Colin Patrick McCabe
         
        56.
        fix narrow race condition in TestPathBasedCacheRequests Sub-task Closed Colin Patrick McCabe
         
        57.
        Rename "path.based" caching configuration options Sub-task Resolved Andrew Wang
         
        58.
        add some more NameNode cache statistics, cache pool stats Sub-task Closed Colin Patrick McCabe
         
        59.
        Refactor tests in TestCacheDirectives Sub-task Resolved Andrew Wang
         
        60.
        CacheAdmin help should match against non-dashed commands Sub-task Closed Andrew Wang
         
        61.
        Namenode loops caching and uncaching when data should be uncached Sub-task Closed Andrew Wang
         
        62.
        Hook up cache directive and pool usage statistics Sub-task Closed Andrew Wang
         
        63.
        allow BlockReaderLocal to switch between checksumming and not Sub-task Closed Colin Patrick McCabe
         
        64.
        Enforce a max TTL per cache pool Sub-task Closed Andrew Wang
         
        65.
        Remove dfs.namenode.caching.enabled and improve CRM locking Sub-task Closed Colin Patrick McCabe
         
        66.
        The CacheManager throws a NPE in the DataNode logs when processing cache reports that refer to a block not known to the BlockManager Sub-task Closed Colin Patrick McCabe
         

          Activity

          Hide
          Andrew Wang added a comment -

          Here's a design doc that we've been working on internally. It proposes adding off-heap caches to each datanode using mmap and mlock, managed centrally by the NameNode.

          Any feedback welcomed. I'm hoping we can have a fruitful design discussion on this JIRA, then perhaps get a branch and start development.

          Show
          Andrew Wang added a comment - Here's a design doc that we've been working on internally. It proposes adding off-heap caches to each datanode using mmap and mlock, managed centrally by the NameNode. Any feedback welcomed. I'm hoping we can have a fruitful design discussion on this JIRA, then perhaps get a branch and start development.
          Hide
          Sanjay Radia added a comment -

          I think we can treat the RAM copies as replicas - this fits into the generalized tiered-storage architecture as described in HDFS-2832 (Ram, flash, disk.)

          • Block reports will indicate the storage type.
          • NN will store the storage type in the Block map
          • Block locations returned by NN to client will have storage type (i.e. don't need the IsCached flag).
            • NN will order the replicas locations based on closeness and speed; this will mean that the client side will automatically go to the best place (although we can have a smarter client do something different if desired.)
          • NN will not count Ram replicas towards the normal replica count - this is one area where the ram replicas are treated differently.
          • This can support a usage model where the ram replicas are at each or only some of the disk replica locations.
          Show
          Sanjay Radia added a comment - I think we can treat the RAM copies as replicas - this fits into the generalized tiered-storage architecture as described in HDFS-2832 (Ram, flash, disk.) Block reports will indicate the storage type. NN will store the storage type in the Block map Block locations returned by NN to client will have storage type (i.e. don't need the IsCached flag). NN will order the replicas locations based on closeness and speed; this will mean that the client side will automatically go to the best place (although we can have a smarter client do something different if desired.) NN will not count Ram replicas towards the normal replica count - this is one area where the ram replicas are treated differently. This can support a usage model where the ram replicas are at each or only some of the disk replica locations.
          Hide
          Colin Patrick McCabe added a comment -

          I agree that there are some commonalities between the hierarchical storage management work and what we're doing here.

          However, tiered storage management schemes put an entire block into a tier. This is different than what we want to (eventually) do with caching, which is cache only part of a block. If we end up with a heavyweight scheme where the entire block has to be loaded into memory before any of it can be accessed, this may actually cause a performance regression, not an improvement.

          In general, tiered storage management happens over a longer period of time than cache management. We need to be responsive to changes that happen in just a few seconds. In contrast, moving things from (say) hard disk to SSD and back will happen over minutes or hours. The same code is not going to be able to handle both well.

          The proposed implementations are quite different, as well. HSM will involve copying block files between local FS directories. Cache management will involve mlock'ing block files and passing the file descriptors to clients. You might well ask, "why not simply copy the block file to /dev/shm for your implementation?" However, this has the "all or nothing" problem described above (can't cache a partial block this way). It also has a more subtle problem with what we are calling "revocation." Basically, a misbehaving client which holds an open file descriptor in /dev/shm can continue to use memory indefinitely-- there is no way the DataNode can ever revoke that memory. This problem does not exist with the mlock solution which we have outlined here.

          So while I think we should consider the possibility of sharing code as the two projects progress, I don't want to make this a subtask of that project. There are just too many differences in goals and approaches for it to make sense.

          Show
          Colin Patrick McCabe added a comment - I agree that there are some commonalities between the hierarchical storage management work and what we're doing here. However, tiered storage management schemes put an entire block into a tier. This is different than what we want to (eventually) do with caching, which is cache only part of a block. If we end up with a heavyweight scheme where the entire block has to be loaded into memory before any of it can be accessed, this may actually cause a performance regression, not an improvement. In general, tiered storage management happens over a longer period of time than cache management. We need to be responsive to changes that happen in just a few seconds. In contrast, moving things from (say) hard disk to SSD and back will happen over minutes or hours. The same code is not going to be able to handle both well. The proposed implementations are quite different, as well. HSM will involve copying block files between local FS directories. Cache management will involve mlock'ing block files and passing the file descriptors to clients. You might well ask, "why not simply copy the block file to /dev/shm for your implementation?" However, this has the "all or nothing" problem described above (can't cache a partial block this way). It also has a more subtle problem with what we are calling "revocation." Basically, a misbehaving client which holds an open file descriptor in /dev/shm can continue to use memory indefinitely-- there is no way the DataNode can ever revoke that memory. This problem does not exist with the mlock solution which we have outlined here. So while I think we should consider the possibility of sharing code as the two projects progress, I don't want to make this a subtask of that project. There are just too many differences in goals and approaches for it to make sense.
          Hide
          Andrew Wang added a comment -

          Sanjay, thanks for your comments! I need to look more at HDFS-2832, but I think we've got some nice overlap. Particularly, I agree that cache would be just another DN Storage.

          Block reports will indicate the storage type.

          I'm ok with this, but our initial design proposes separate heartbeats since cache reports might want to tick on a different interval. You might want quick cache reports if datanodes are doing their own LRU, but maybe you'd want to adaptively throttle it back if the NN is under load, since cache report processing can be expensive.

          Separate heartbeats per-storage could definitely be added in later, so consider this a later-stage optimization.

          NN will order the replicas locations based on closeness and speed;

          This is tricky because it depends on the network topology and workload. I don't want my single cached replica to get hammered by the entire cluster, but perhaps going to in-rack memory is better than local disk. I figure clients should be able to provide a configurable policy to their DFSClients.

          I think we also still need the isCached flag for scheduling. Hypothetically, MR might always want to place on a memory replica over a disk replica. So, we could sort memory replicas first, then disk replicas. However, this squishes the existing ordering based on network topology used by DFSClients, and all our DFSClients end up hammering the cached replica at read time.

          Note that even without a smarter DFSClient, we can get a lot of benefit just by making schedulers place tasks for memory-locality since our big win is going to be local memory reads. Colin's working on this in HDFS-4952.

          NN will not count Ram replicas towards the normal replica count - this is one area where the ram replicas are treated differently.

          This can support a usage model where the ram replicas are at each or only some of the disk replica locations.

          +1, let's design for a future where cache might not be disk-backed. As Colin notes above, memory HSM is not easy, but the code should be flexible.

          Show
          Andrew Wang added a comment - Sanjay, thanks for your comments! I need to look more at HDFS-2832 , but I think we've got some nice overlap. Particularly, I agree that cache would be just another DN Storage. Block reports will indicate the storage type. I'm ok with this, but our initial design proposes separate heartbeats since cache reports might want to tick on a different interval. You might want quick cache reports if datanodes are doing their own LRU, but maybe you'd want to adaptively throttle it back if the NN is under load, since cache report processing can be expensive. Separate heartbeats per-storage could definitely be added in later, so consider this a later-stage optimization. NN will order the replicas locations based on closeness and speed; This is tricky because it depends on the network topology and workload. I don't want my single cached replica to get hammered by the entire cluster, but perhaps going to in-rack memory is better than local disk. I figure clients should be able to provide a configurable policy to their DFSClients. I think we also still need the isCached flag for scheduling. Hypothetically, MR might always want to place on a memory replica over a disk replica. So, we could sort memory replicas first, then disk replicas. However, this squishes the existing ordering based on network topology used by DFSClients, and all our DFSClients end up hammering the cached replica at read time. Note that even without a smarter DFSClient, we can get a lot of benefit just by making schedulers place tasks for memory-locality since our big win is going to be local memory reads. Colin's working on this in HDFS-4952 . NN will not count Ram replicas towards the normal replica count - this is one area where the ram replicas are treated differently. This can support a usage model where the ram replicas are at each or only some of the disk replica locations. +1, let's design for a future where cache might not be disk-backed. As Colin notes above, memory HSM is not easy, but the code should be flexible.
          Hide
          Suresh Srinivas added a comment -

          However, tiered storage management schemes put an entire block into a tier. This is different than what we want to (eventually) do with caching, which is cache only part of a block. If we end up with a heavyweight scheme where the entire block has to be loaded into memory before any of it can be accessed, this may actually cause a performance regression, not an improvement.

          This is one point I have been mulling over as well. I agree, partially cached data does not fit with storage hierarchy. But I was not sure partial cache is being consider in the first phase of implementation in this jira (sorry I am yet to read this carefully, If i missed details).

          One other thing that we are considering is usage based extra replica to memory tier. Need to make some time to get that all into a doc.

          Show
          Suresh Srinivas added a comment - However, tiered storage management schemes put an entire block into a tier. This is different than what we want to (eventually) do with caching, which is cache only part of a block. If we end up with a heavyweight scheme where the entire block has to be loaded into memory before any of it can be accessed, this may actually cause a performance regression, not an improvement. This is one point I have been mulling over as well. I agree, partially cached data does not fit with storage hierarchy. But I was not sure partial cache is being consider in the first phase of implementation in this jira (sorry I am yet to read this carefully, If i missed details). One other thing that we are considering is usage based extra replica to memory tier. Need to make some time to get that all into a doc.
          Hide
          Todd Lipcon added a comment -

          Hey folks. I agree that HSM is a much bigger task than what we're talking about here, and not certain they can fit into the same framework. During our early internal design discussions I'd suggested the same thing, but after an hour or two of throwing the idea around, we discounted it due to the reasons Colin mentioned above (partial caching and revocation).

          Though partial caching isn't referenced in the doc, it's a straightforward extension that we plan to tackle down the road. For example, we can take each block, subdivide into 1MB chunks, and then report a bitmap indicating which chunks are cached. Taking advantage of the kernel lets us do this relatively easily calling mlock/munlock – and the revocation problem is again simple because a misbehaving client won't be able to pin memory.

          I don't think this work precludes later work on the idea of memory-only storages/replicas. That has other advantages, particularly on the write side for temporary data, etc. But is somewhat tricky to get right. When we do that, we should certainly look at it in a generalized way (RAM, SSD, Disk as a hierarchy).

          Show
          Todd Lipcon added a comment - Hey folks. I agree that HSM is a much bigger task than what we're talking about here, and not certain they can fit into the same framework. During our early internal design discussions I'd suggested the same thing, but after an hour or two of throwing the idea around, we discounted it due to the reasons Colin mentioned above (partial caching and revocation). Though partial caching isn't referenced in the doc, it's a straightforward extension that we plan to tackle down the road. For example, we can take each block, subdivide into 1MB chunks, and then report a bitmap indicating which chunks are cached. Taking advantage of the kernel lets us do this relatively easily calling mlock/munlock – and the revocation problem is again simple because a misbehaving client won't be able to pin memory. I don't think this work precludes later work on the idea of memory-only storages/replicas. That has other advantages, particularly on the write side for temporary data, etc. But is somewhat tricky to get right. When we do that, we should certainly look at it in a generalized way (RAM, SSD, Disk as a hierarchy).
          Hide
          Suresh Srinivas added a comment -

          The problem for partical cache is though, while at file level or directory level it is easy to address the data to be cached, more granular level means that the cache management layer (hopefully I would like see it in namenode) will cause bloat in how much data must be tracked in cache manager.

          How about making use of access patterns and build it instead of managed cache?

          Show
          Suresh Srinivas added a comment - The problem for partical cache is though, while at file level or directory level it is easy to address the data to be cached, more granular level means that the cache management layer (hopefully I would like see it in namenode) will cause bloat in how much data must be tracked in cache manager. How about making use of access patterns and build it instead of managed cache?
          Hide
          Todd Lipcon added a comment -

          Yes, I think the explicit caching policies would operate mostly on a whole-file granularity. The DNs, though, can do local LRU tracking of sub-blocks. This is useful for cases like querying a Parquet file where a single file is made up of subranges corresponding to different columns. Some columns may be hot while others are cold, and if the DN can notice this and start offering zero-copy for the hot columns, it will be a significant performance win.

          Show
          Todd Lipcon added a comment - Yes, I think the explicit caching policies would operate mostly on a whole-file granularity. The DNs, though, can do local LRU tracking of sub-blocks. This is useful for cases like querying a Parquet file where a single file is made up of subranges corresponding to different columns. Some columns may be hot while others are cold, and if the DN can notice this and start offering zero-copy for the hot columns, it will be a significant performance win.
          Hide
          Chu Tong added a comment -

          To maximize memory usage, should we consider to compress file blocks before caching them in memory?

          Show
          Chu Tong added a comment - To maximize memory usage, should we consider to compress file blocks before caching them in memory?
          Hide
          Colin Patrick McCabe added a comment -

          For most of the applications we're considering here, compression would not be a win, because it is CPU-intensive. It also would involve copying the data in memory, which is one of the things we're trying to avoid here. I think it will be more effective to use something like CompressionCodec, ORC, Parquet, rcfile, etc.

          Show
          Colin Patrick McCabe added a comment - For most of the applications we're considering here, compression would not be a win, because it is CPU-intensive. It also would involve copying the data in memory, which is one of the things we're trying to avoid here. I think it will be more effective to use something like CompressionCodec, ORC, Parquet, rcfile, etc.
          Hide
          Sanjay Radia added a comment -

          Caching partial blocks: There is no problem with a DN caching only the hot parts of a block and still declaring to the NN that the block is cached in ram. This would fit in with the proposal of abstracting ram copies as replicas. The use case that does not fit in is where DN1 has cached the first 100 bytes and and Datanode, DN2 has cached the last 100 bytes and you want the client to go to the right data node based on what portion of the file it is reading. If and when we finally get to caching portions and we want to support the use case mentioned, we, at that time, could considering the block-info sent for RAM replicas to indicate what portion are cached – this would mean that certain replicas have additional in the block map.

          Given that we are not caching portions of block for this Jira and that for tiered storage for SSDs we want to add the device info to block location, I suggest that we proceed with abstracting RAM copies as replicas and later revisit this decision for partial block caching at a later point.

          Show
          Sanjay Radia added a comment - Caching partial blocks: There is no problem with a DN caching only the hot parts of a block and still declaring to the NN that the block is cached in ram. This would fit in with the proposal of abstracting ram copies as replicas. The use case that does not fit in is where DN1 has cached the first 100 bytes and and Datanode, DN2 has cached the last 100 bytes and you want the client to go to the right data node based on what portion of the file it is reading. If and when we finally get to caching portions and we want to support the use case mentioned, we, at that time, could considering the block-info sent for RAM replicas to indicate what portion are cached – this would mean that certain replicas have additional in the block map. Given that we are not caching portions of block for this Jira and that for tiered storage for SSDs we want to add the device info to block location, I suggest that we proceed with abstracting RAM copies as replicas and later revisit this decision for partial block caching at a later point.
          Hide
          Colin Patrick McCabe added a comment -

          As Todd, Andrew, and I said before, all of the designs we considered that treated what was in the cache as replicas suffered from an inability to revoke the client's access to this memory. If you pass the client a file descriptor to a file in /dev/shm, you cannot revoke access to that later on. The client can hold on to that memory forever. That alone is enough to throw out that design.

          To avoid this, we have to use mmap of a file on disk. And when you do that, it can no longer be abstracted as a replica, because the on-disk copy has to exist. It is at best, a property of an existing replica.

          Just as important, caching decisions also have to be made on a different timescale than decisions about hierarchical storage management. HSM decisions can be made over the course of minutes or hours; caching decisions have to be made in seconds to be relevant.

          Memory is not a storage tier. It doesn't store anything; rather, it caches. Does it make sense to fsck memory? That is silly.

          Show
          Colin Patrick McCabe added a comment - As Todd, Andrew, and I said before, all of the designs we considered that treated what was in the cache as replicas suffered from an inability to revoke the client's access to this memory. If you pass the client a file descriptor to a file in /dev/shm , you cannot revoke access to that later on. The client can hold on to that memory forever. That alone is enough to throw out that design. To avoid this, we have to use mmap of a file on disk. And when you do that, it can no longer be abstracted as a replica, because the on-disk copy has to exist. It is at best, a property of an existing replica. Just as important, caching decisions also have to be made on a different timescale than decisions about hierarchical storage management. HSM decisions can be made over the course of minutes or hours; caching decisions have to be made in seconds to be relevant. Memory is not a storage tier. It doesn't store anything; rather, it caches. Does it make sense to fsck memory? That is silly.
          Hide
          Sanjay Radia added a comment -

          we have to use mmap of a file on disk.

          Please look at my comments: I have not objected to mmap and mlock.
          I am fine with having Ram replicas backed by disk replica; indeed I see this as an important advantage over Ramfs where the data is copied. The replication abstractions allows for a more general view where they are not, but our implementation restricts the memory replicas to be backed by disk replicas.

          In general, tiered storage management happens over a longer period of time than cache management.

          The term tier-storage is unfortunate (I misused it in my original comment). In HDFS-2832, we consciously used the terms "heterogeneous storage" and not tiered storage. Tiering as in "moving things based on their hotness" is policy. (BTW I envision using SSDs initially not for moving hot blocks but as storage for one of 3 replicas. I have discussed this use case with a few of the HBase folks). Caching is a use case that applies well to disks vs ram. Both the use cases apply well to the abstraction of replicas stored on different kinds of storage devices.

          Memory is not a storage tier. It doesn't store anything; rather, it caches. Does it make sense to fsck memory? That is silly.

          Memory and disks store data but one is way more durable. Fsck is a bad example - you do fsck on a file system not on the disk. Here we are taking about entities that store HDFS block data. But this debate over the similarities and difference between ram and disk is a longer one that we should have over beer. I am not blind to the differences between disks and ram. Further, by using the same abstraction to model ram copies and disk copies does not mean that I am implying that I am going to always treat them as exactly the same and ignore the differences.

          Show
          Sanjay Radia added a comment - we have to use mmap of a file on disk. Please look at my comments: I have not objected to mmap and mlock. I am fine with having Ram replicas backed by disk replica; indeed I see this as an important advantage over Ramfs where the data is copied. The replication abstractions allows for a more general view where they are not, but our implementation restricts the memory replicas to be backed by disk replicas. In general, tiered storage management happens over a longer period of time than cache management. The term tier-storage is unfortunate (I misused it in my original comment). In HDFS-2832 , we consciously used the terms "heterogeneous storage" and not tiered storage. Tiering as in "moving things based on their hotness" is policy. (BTW I envision using SSDs initially not for moving hot blocks but as storage for one of 3 replicas. I have discussed this use case with a few of the HBase folks). Caching is a use case that applies well to disks vs ram. Both the use cases apply well to the abstraction of replicas stored on different kinds of storage devices. Memory is not a storage tier. It doesn't store anything; rather, it caches. Does it make sense to fsck memory? That is silly. Memory and disks store data but one is way more durable. Fsck is a bad example - you do fsck on a file system not on the disk. Here we are taking about entities that store HDFS block data. But this debate over the similarities and difference between ram and disk is a longer one that we should have over beer. I am not blind to the differences between disks and ram. Further, by using the same abstraction to model ram copies and disk copies does not mean that I am implying that I am going to always treat them as exactly the same and ignore the differences.
          Hide
          Sanjay Radia added a comment -

          To converge on this could we do a meetup?

          Show
          Sanjay Radia added a comment - To converge on this could we do a meetup?
          Hide
          Colin Patrick McCabe added a comment -

          A meetup is a good idea. I will be at OSCON next week on Tuesday, Wednesday, and Thursday, but any other time in the next two weeks is fine with me. I can't speak for Andrew and Todd, but I didn't see anything on the calendar that would block it in that time frame.

          Show
          Colin Patrick McCabe added a comment - A meetup is a good idea. I will be at OSCON next week on Tuesday, Wednesday, and Thursday, but any other time in the next two weeks is fine with me. I can't speak for Andrew and Todd, but I didn't see anything on the calendar that would block it in that time frame.
          Hide
          Suresh Srinivas added a comment -

          As discussed in the comments earlier, few of us are going to meet to discuss the design and issues related to this jira. I have setup a meeting at Hortonworks office. We should be able to host around 15-20 people. I already have Andrew Wang, Arpit Gupta, Aaron T. Myers, Bikas Saha, Colin Patrick McCabe, Sanjay Radia, Suresh Srinivas, Vinod Kumar Vavilapalli, Jing Zhao and gopal as attendees. Others who want to attend the meeting or want to join over the phone, please reach out to me at suresh@hortonworks.com.

          We will post notes from the discussion to this jira.

          Show
          Suresh Srinivas added a comment - As discussed in the comments earlier, few of us are going to meet to discuss the design and issues related to this jira. I have setup a meeting at Hortonworks office. We should be able to host around 15-20 people. I already have Andrew Wang , Arpit Gupta , Aaron T. Myers , Bikas Saha , Colin Patrick McCabe , Sanjay Radia , Suresh Srinivas , Vinod Kumar Vavilapalli , Jing Zhao and gopal as attendees. Others who want to attend the meeting or want to join over the phone, please reach out to me at suresh@hortonworks.com. We will post notes from the discussion to this jira.
          Hide
          David S. Wang added a comment -

          HDFS-4949 meeting, July 29, 2013 2 PM @ Hortonworks office
          ====

          Attendees
          ====

          Aaron T. Myers
          Andrew Wang
          Arpit Gupta
          Bikas Saha
          Brandon Li
          Colin McCabe
          Dave Wang
          Jing Zhao
          Suresh Srinivas
          Sanjay Radia
          Todd Lipcon
          Vinod Kumar Vavilapalli

          Minutes
          ====

          • General agreement to hold HDFS-2832 meeting some other day
          • Andrew: Posted HDFS-4949 design doc upstream; Sanjay has read this, agrees with the goals

          Data path (zero-copy reads)


          • Sanjay: quota mgmt - counted up front, not after cache is populated
          • Colin: talking about ZCR (mmap) - used to implement caching at the DN level
            • Considered copying everything into /dev/shm (e.g. Tachyon). But cannot cache parts of a file, so limits our flexibility. Also, the associated fd gives clients a way to control memory mgmt (will not release until that descriptor is closed), which is not good because of buggy clients etc.
            • Sanjay: you want an abstraction for a durable file. Colin: yes.
            • Colin: ZCR currently doesn't have checksums, but will. Todd: assumption is that DN will do the cksum when doing the mlock and communicate that to the client so the client knows that it's safe to read.
            • Todd: mincore() can tell you what's already in cache, but it's too granular, very expensive to call, and can be out-of-date immediately.
            • Assuming this is for local clients only obviously.
            • ZCR uses ByteBuffers to avoid copies. Not entirely compatible with current DFSClient since that uses byte arrays, so you cannot avoid copies.
          • This may have a conflict with inline checksums. Clients would have to be aware of how to skip over checksums, and this would have to be in the app, not the client since we're talking mmap.
            • HBase gets around this by disabling HDFS-level cksums, and doing it on their level.
            • Sanjay: QFS puts all of the cksums in the beginning of the file
            • Todd: Liang Xie had an HBase study where he figured out that perf didn't improve until he got to a TB of data, when the cksum files themselves dropped out ofcache.
          • ZCR API can be made public? Colin, Todd: Yes.
            • Hard to compete with Spark if this isn't public.
            • Suresh: Will the app know if you got ZCR? Can be added as counters. Colin: already have similar concepts today for SCR on a per-stream basis.
            • Todd: SCR is fully transparent (uses today's API), while ZCR requires new client API.
          • Sanjay: Current policy is manual. Later policy can have system automatically cache hot files. Need the fallback buffer in case you are remote.
            • Todd: high perf apps will always use the ZCR API. Sometimes it will fall back to a normal read, so no worse than today.
            • Colin: should we have a flag that basically says "always mmap"? Can add it later, don't know how useful this could be.
          • Colin: no native support required for ZCR beyond what is there today. There are some libhdfs changes, but not completely required. Java has mmap today.
            • We will need a native call for locking though.

          Centralized cache mgmt


          • Andrew gave whiteboard presentation
            • DN has mlock hooks, ulimit conf of how much it can cache
            • NN sends heartbeats to DN with cache/uncache commands on whole blocks
            • DN will send cache state to NN similar to block reports
            • clients call getFileBlockLocations() with storageType arg. This returns the current state of the cache.
            • clients can issue CachingRequests, with a path that points to a file or directory. If directory, then what is cached is what's in that directory (but not recurse to subdirs), in order to support Hive. Can also specify user, pool for quote mgmt. Can also specify # cache copies (must be <= replicationFactor).
          • Quotas
            • Quotas are on pools, not users. Quotas enforced on the NN.
            • Questions about what is cached as machines come and go? Use getFileBlockLocations() to get cache request and current status of fulfillment. Can be not fulfilled due to quota for instance.
              • Should cache requests from two pools be counted fully against both? Half-half? Cluster capacity can be dynamic, so you always have potential quote mgmt problems.
            • Don't want to get this so complicated so that you basically are implementing another scheduler just for cache quotas.
            • Suresh: Resource failures - how does this affect the pools? Should we have priorities for pools? Priorities for individual CacheRequests?
            • Andrew: suggestion of min/max/share (similar to VMware ESX VM memory configuration).
            • Suresh: fine with doing something very basic, and then be more intelligent later.
            • Sanjay: need to have some idea of per-pool priority to enforce min, to figure out what to evict from the cache first in mem-constrained scenarios. Also what happens once we have resources again?
          • Suresh: don't cache files being written to? ATM, others: yes.
          • Cache entire files vs. shares of files in a request that can't be 100% satisfied? Yes.
          • Interaction with symlinks? Discuss on JIRA.
          • Suresh: only cache something that is local to DN? Yes.
          • Sanjay: should block reports should include storage types? ATM: Treat RAM as a special case at least for now (e.g. have a bit that indicates that this replica is in RAM).
          • Sanjay: leases for the CacheRequests? Todd: CacheRequests could have their status listed as a API call, not a lease. Otherwise clients have to keep requesting renewals, which sucks for existing folks like Hive.
            • Suresh: how about a expiry time in the CacheRequest?
          • Sanjay: Question about how big the RPCs are from NN -> DN
            • Todd: assuming 10 MB blocks, and 100 GB cache memory for a DN, then max of 10K blocks in an RPC. But will be smaller due to incremental reports.
            • Suresh: perhaps push down idea of collection id to DN, so NN can just say "evict this collection" instead of having to send evicts for all of the blocks. Can be addressed later in a compatible fashion.
          • Suresh: how can we help?
            • Colin: review on the ZCR would be great.
            • Andrew: HDFS-4949: will start churning on this ASAP, over the next month. Could use some help with testing.
          • Suresh: branch to put this in? 2.3? That's where all of the feature work is going.
          Show
          David S. Wang added a comment - HDFS-4949 meeting, July 29, 2013 2 PM @ Hortonworks office ==== Attendees ==== Aaron T. Myers Andrew Wang Arpit Gupta Bikas Saha Brandon Li Colin McCabe Dave Wang Jing Zhao Suresh Srinivas Sanjay Radia Todd Lipcon Vinod Kumar Vavilapalli Minutes ==== General agreement to hold HDFS-2832 meeting some other day Andrew: Posted HDFS-4949 design doc upstream; Sanjay has read this, agrees with the goals Data path (zero-copy reads) Sanjay: quota mgmt - counted up front, not after cache is populated Colin: talking about ZCR (mmap) - used to implement caching at the DN level Considered copying everything into /dev/shm (e.g. Tachyon). But cannot cache parts of a file, so limits our flexibility. Also, the associated fd gives clients a way to control memory mgmt (will not release until that descriptor is closed), which is not good because of buggy clients etc. Sanjay: you want an abstraction for a durable file. Colin: yes. Colin: ZCR currently doesn't have checksums, but will. Todd: assumption is that DN will do the cksum when doing the mlock and communicate that to the client so the client knows that it's safe to read. Todd: mincore() can tell you what's already in cache, but it's too granular, very expensive to call, and can be out-of-date immediately. Assuming this is for local clients only obviously. ZCR uses ByteBuffers to avoid copies. Not entirely compatible with current DFSClient since that uses byte arrays, so you cannot avoid copies. This may have a conflict with inline checksums. Clients would have to be aware of how to skip over checksums, and this would have to be in the app, not the client since we're talking mmap. HBase gets around this by disabling HDFS-level cksums, and doing it on their level. Sanjay: QFS puts all of the cksums in the beginning of the file Todd: Liang Xie had an HBase study where he figured out that perf didn't improve until he got to a TB of data, when the cksum files themselves dropped out ofcache. ZCR API can be made public? Colin, Todd: Yes. Hard to compete with Spark if this isn't public. Suresh: Will the app know if you got ZCR? Can be added as counters. Colin: already have similar concepts today for SCR on a per-stream basis. Todd: SCR is fully transparent (uses today's API), while ZCR requires new client API. Sanjay: Current policy is manual. Later policy can have system automatically cache hot files. Need the fallback buffer in case you are remote. Todd: high perf apps will always use the ZCR API. Sometimes it will fall back to a normal read, so no worse than today. Colin: should we have a flag that basically says "always mmap"? Can add it later, don't know how useful this could be. Colin: no native support required for ZCR beyond what is there today. There are some libhdfs changes, but not completely required. Java has mmap today. We will need a native call for locking though. Centralized cache mgmt Andrew gave whiteboard presentation DN has mlock hooks, ulimit conf of how much it can cache NN sends heartbeats to DN with cache/uncache commands on whole blocks DN will send cache state to NN similar to block reports clients call getFileBlockLocations() with storageType arg. This returns the current state of the cache. clients can issue CachingRequests, with a path that points to a file or directory. If directory, then what is cached is what's in that directory (but not recurse to subdirs), in order to support Hive. Can also specify user, pool for quote mgmt. Can also specify # cache copies (must be <= replicationFactor). Quotas Quotas are on pools, not users. Quotas enforced on the NN. Questions about what is cached as machines come and go? Use getFileBlockLocations() to get cache request and current status of fulfillment. Can be not fulfilled due to quota for instance. Should cache requests from two pools be counted fully against both? Half-half? Cluster capacity can be dynamic, so you always have potential quote mgmt problems. Don't want to get this so complicated so that you basically are implementing another scheduler just for cache quotas. Suresh: Resource failures - how does this affect the pools? Should we have priorities for pools? Priorities for individual CacheRequests? Andrew: suggestion of min/max/share (similar to VMware ESX VM memory configuration). Suresh: fine with doing something very basic, and then be more intelligent later. Sanjay: need to have some idea of per-pool priority to enforce min, to figure out what to evict from the cache first in mem-constrained scenarios. Also what happens once we have resources again? Suresh: don't cache files being written to? ATM, others: yes. Cache entire files vs. shares of files in a request that can't be 100% satisfied? Yes. Interaction with symlinks? Discuss on JIRA. Suresh: only cache something that is local to DN? Yes. Sanjay: should block reports should include storage types? ATM: Treat RAM as a special case at least for now (e.g. have a bit that indicates that this replica is in RAM). Sanjay: leases for the CacheRequests? Todd: CacheRequests could have their status listed as a API call, not a lease. Otherwise clients have to keep requesting renewals, which sucks for existing folks like Hive. Suresh: how about a expiry time in the CacheRequest? Sanjay: Question about how big the RPCs are from NN -> DN Todd: assuming 10 MB blocks, and 100 GB cache memory for a DN, then max of 10K blocks in an RPC. But will be smaller due to incremental reports. Suresh: perhaps push down idea of collection id to DN, so NN can just say "evict this collection" instead of having to send evicts for all of the blocks. Can be addressed later in a compatible fashion. Suresh: how can we help? Colin: review on the ZCR would be great. Andrew: HDFS-4949 : will start churning on this ASAP, over the next month. Could use some help with testing. Suresh: branch to put this in? 2.3? That's where all of the feature work is going.
          Hide
          Colin Patrick McCabe added a comment -

          I created a branch for this (HDFS-4949)

          Show
          Colin Patrick McCabe added a comment - I created a branch for this ( HDFS-4949 )
          Hide
          Suresh Srinivas added a comment - - edited

          My notes from the meeting:
          Enabling this feature on windows platform requires the following:

          1. Need Unix Domain sockets equivalent
          2. mmap and munmap is done using java and should not require any windows specific changes
          3. mlock there is no windows equivalent?

          Quota for datanode cache is counted against pool

          Design needs to cover the following scenarios in more detail:

          1. Two pools caching the same file and how is quota counted
          2. Resource failures and how it affects existing caches for the pools. Perhaps pools should have priorities.
            • scenario 1 - resource failure takes down cached data. In the first cut, no new cached replicas will be created.
            • scenario 2 - resources failed and cluster capacity is low, then the application even if higher priority will not get cache quota.
          3. Caching supported for whole file for now.
          4. Only completed blocks will be cached. This is true for files that are being written.
          5. symlink paths will not be cached
          6. Need to add more details on enabling cache for a directory and how the newly created files (on completion of write) will be added to the cache. This also has quota implications and need for handling failures related to either reaching quota or non-availability of resources for such automatic caching to work.

          We should add TTL for caching request and expire the cache.

          Lets refresh the design document based on discussions from the meeting.

          Show
          Suresh Srinivas added a comment - - edited My notes from the meeting: Enabling this feature on windows platform requires the following: Need Unix Domain sockets equivalent mmap and munmap is done using java and should not require any windows specific changes mlock there is no windows equivalent? Quota for datanode cache is counted against pool Design needs to cover the following scenarios in more detail: Two pools caching the same file and how is quota counted Resource failures and how it affects existing caches for the pools. Perhaps pools should have priorities. scenario 1 - resource failure takes down cached data. In the first cut, no new cached replicas will be created. scenario 2 - resources failed and cluster capacity is low, then the application even if higher priority will not get cache quota. Caching supported for whole file for now. Only completed blocks will be cached. This is true for files that are being written. symlink paths will not be cached Need to add more details on enabling cache for a directory and how the newly created files (on completion of write) will be added to the cache. This also has quota implications and need for handling failures related to either reaching quota or non-availability of resources for such automatic caching to work. We should add TTL for caching request and expire the cache. Lets refresh the design document based on discussions from the meeting.
          Hide
          Chris Nauroth added a comment -

          mlock there is no windows equivalent?

          I believe the Windows equivalent of mlock and munlock are VirtualLock and VirtualUnlock.

          http://msdn.microsoft.com/en-us/library/windows/desktop/aa366895(v=vs.85).aspx

          http://msdn.microsoft.com/en-us/library/windows/desktop/aa366910(v=vs.85).aspx

          Show
          Chris Nauroth added a comment - mlock there is no windows equivalent? I believe the Windows equivalent of mlock and munlock are VirtualLock and VirtualUnlock . http://msdn.microsoft.com/en-us/library/windows/desktop/aa366895(v=vs.85).aspx http://msdn.microsoft.com/en-us/library/windows/desktop/aa366910(v=vs.85).aspx
          Hide
          Tsuyoshi Ozawa added a comment -

          Hi,

          Are there any plan to add APIs to access this caching layer directly from processing framework - e.g. MR? RDD(Spark) paper says that serialization/deserialization of file contents can be the bottleneck of processing. If we have such general APIs using mlock/munlock, it can reduce processing time drastically. Or, this idea is out of scope of this JIRA?

          Show
          Tsuyoshi Ozawa added a comment - Hi, Are there any plan to add APIs to access this caching layer directly from processing framework - e.g. MR? RDD(Spark) paper says that serialization/deserialization of file contents can be the bottleneck of processing. If we have such general APIs using mlock/munlock, it can reduce processing time drastically. Or, this idea is out of scope of this JIRA?
          Hide
          Andrew Wang added a comment -

          Hi Tsuyoshi,

          HDFS-4953 allows applications to do zero-copy reads, so when combined with this JIRA, HDFS will be able to provide full memory-bandwidth reads on cached data. Deserialization is a somewhat separate concern since it happens at the application-level though. If an app can operate directly on the raw bytes in a file (e.g. a ByteBuffer), then it can avoid deserialization overhead. IIUC, this is untrue of the current MR input formats.

          Show
          Andrew Wang added a comment - Hi Tsuyoshi, HDFS-4953 allows applications to do zero-copy reads, so when combined with this JIRA, HDFS will be able to provide full memory-bandwidth reads on cached data. Deserialization is a somewhat separate concern since it happens at the application-level though. If an app can operate directly on the raw bytes in a file (e.g. a ByteBuffer), then it can avoid deserialization overhead. IIUC, this is untrue of the current MR input formats.
          Hide
          Andrew Wang added a comment -

          Suresh, thanks for posting your notes. Attached is a revised design doc that beefs up the resource management / user quotas section, as well as addressing your other smaller points.

          As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going. I think it's reasonable for the first iteration to do something simple like "superuser only" or user quotas, then we layer on the complexities of pools, priorities, ACLs, min/max/share, and failure cases afterwards. It's good to get the API roughly right so we code with foresight, but I don't see us getting around to implementing pools for at least a month or two.

          Show
          Andrew Wang added a comment - Suresh, thanks for posting your notes. Attached is a revised design doc that beefs up the resource management / user quotas section, as well as addressing your other smaller points. As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going. I think it's reasonable for the first iteration to do something simple like "superuser only" or user quotas, then we layer on the complexities of pools, priorities, ACLs, min/max/share, and failure cases afterwards. It's good to get the API roughly right so we code with foresight, but I don't see us getting around to implementing pools for at least a month or two.
          Hide
          Suresh Srinivas added a comment -

          As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going.

          +1 for this. There are many loose ends to be tied and details to be figured out in the design. But the basic implementation could start right away.

          Some things that we should get to sooner than later:

          • Pool abstraction and making sure all the APIs are using them (including cache creation and deletion)
          • Some details related to how the stream oriented APIs change to buffer oriented access.

          The real quota management, counting common cached data to different pools etc. can be revisited later. Will take a look at the updated doc soon. Thanks Andrew.

          Show
          Suresh Srinivas added a comment - As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going. +1 for this. There are many loose ends to be tied and details to be figured out in the design. But the basic implementation could start right away. Some things that we should get to sooner than later: Pool abstraction and making sure all the APIs are using them (including cache creation and deletion) Some details related to how the stream oriented APIs change to buffer oriented access. The real quota management, counting common cached data to different pools etc. can be revisited later. Will take a look at the updated doc soon. Thanks Andrew.
          Hide
          Arun C Murthy added a comment -

          As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going.

          Makes sense.

          I, for one, would volunteer to help you guys do resource-management directly via YARN rather than go the route of inventing half of YARN RM within HDFS. It would benefit both HDFS (simpler, plus ability to use memory dynamically between applications and for caching) & YARN (more robust for a diverse set of applications). Any takers? Thanks.

          Show
          Arun C Murthy added a comment - As a meta-point, I think much of the remaining resource management design can wait until after we get the initial end-to-end implementation going. Makes sense. I, for one, would volunteer to help you guys do resource-management directly via YARN rather than go the route of inventing half of YARN RM within HDFS. It would benefit both HDFS (simpler, plus ability to use memory dynamically between applications and for caching) & YARN (more robust for a diverse set of applications). Any takers? Thanks.
          Hide
          Arun C Murthy added a comment -

          Andrew Wang overall it's looks great, some more questions:

          1. I'm not sure you want to automatically add new files in a directory to the cache, it seems a higher-level system (Hive, Impala, HCat) are in better position. Not doing this automatically simplifies cache mgmt, quota mgmt etc.
          2. Can you please provide details on the read apis? For the Hive/MR/Pig use case I'd like to see a new open(Path, offset, length) which returns an indicator for whether the block is cached or not. This, for e.g., would be used by the RecordReader to read the split.
          Show
          Arun C Murthy added a comment - Andrew Wang overall it's looks great, some more questions: I'm not sure you want to automatically add new files in a directory to the cache, it seems a higher-level system (Hive, Impala, HCat) are in better position. Not doing this automatically simplifies cache mgmt, quota mgmt etc. Can you please provide details on the read apis? For the Hive/MR/Pig use case I'd like to see a new open(Path, offset, length) which returns an indicator for whether the block is cached or not. This, for e.g., would be used by the RecordReader to read the split.
          Hide
          Andrew Wang added a comment -

          Hey Arun, thanks for taking a look!

          Tying in YARN would definitely be great. There's half a hope that we can jump right from a prototype naive scheme to using YARN directly, but our resource management team doesn't have time in the near term to make this happen. I definitely want our abstractions to be as similar as possible though to ease a future transition; your input there is appreciated.

          As to your other points:

          1. The main reason we added auto-caching of new files was actually for Hive. My understanding is that Hive users can drop new files into a Hive partition directory without notifying the Hive metastore, e.g. via the fs shell. Since we'd like to provide the abstraction of caching higher-level abstractions like Hive partitions or tables, this auto-caching is necessary.
          2. We were planning on extending the existing getFileBlockLocations API (which takes a Path, offset, and length) to also indicate which replicas of the returned blocks are cached. This should satisfy the needs of framework schedulers like MR or Impala. At read time, we'll also provide per-stream statistics of the number of bytes read remotely vs. local disk vs. local memory. Remote memory reads are also on our mind, but will likely be a per-stream or per-client config option added later.

          Suresh, to partially address your questions, Colin's going to put pools into the patch at HDFS-5052, and he's also been working on buffer-oriented access at HDFS-4953. Thanks for your comments on the subtasks thus far.

          Show
          Andrew Wang added a comment - Hey Arun, thanks for taking a look! Tying in YARN would definitely be great. There's half a hope that we can jump right from a prototype naive scheme to using YARN directly, but our resource management team doesn't have time in the near term to make this happen. I definitely want our abstractions to be as similar as possible though to ease a future transition; your input there is appreciated. As to your other points: 1. The main reason we added auto-caching of new files was actually for Hive. My understanding is that Hive users can drop new files into a Hive partition directory without notifying the Hive metastore, e.g. via the fs shell. Since we'd like to provide the abstraction of caching higher-level abstractions like Hive partitions or tables, this auto-caching is necessary. 2. We were planning on extending the existing getFileBlockLocations API (which takes a Path, offset, and length) to also indicate which replicas of the returned blocks are cached. This should satisfy the needs of framework schedulers like MR or Impala. At read time, we'll also provide per-stream statistics of the number of bytes read remotely vs. local disk vs. local memory. Remote memory reads are also on our mind, but will likely be a per-stream or per-client config option added later. Suresh, to partially address your questions, Colin's going to put pools into the patch at HDFS-5052 , and he's also been working on buffer-oriented access at HDFS-4953 . Thanks for your comments on the subtasks thus far.
          Hide
          Arun C Murthy added a comment -

          1. The main reason we added auto-caching of new files was actually for Hive. My understanding is that Hive users can drop new files into a Hive partition directory without notifying the Hive metastore, e.g. via the fs shell.

          Usually partitions in Hive are new directories. So every 5 or 10 or 15 mins a new directory is added along with new data. Hence, the ability to automatically cache new files seems redundant.

          2. We were planning on extending the existing getFileBlockLocations API (which takes a Path, offset, and length) to also indicate which replicas of the returned blocks are cached. This should satisfy the needs of framework schedulers like MR or Impala.

          Andrew Wang Agree that the enhancement to getFileBlockLocations suffices for the scheduler. However, at read time it will be very useful to get an indicator on whether it's cached or not during open. The RecordReader needs this API to decide whether to do stream-based reads (when data isn't cached in RAM) or mmap the file (when it's cached). It would be unfortunate to have to do another call to getFileBlockLocations to validate during read time.

          For e.g. SequenceFileRecordReader.initialize would look something like:

          SequenceFileRecordReader.java
            public void initialize(InputSplit split, 
                                   TaskAttemptContext context
                                   ) throws IOException, InterruptedException {
          
            // ...
          
            StreamOrCached splitData = split.getPath().open(fileSplit.getStart(), fileSplit.getLength();
            InputStream in = null;
            if (in.isCached()) {
              in = new ByteBufferInputStream(splitData.getByteBuffer());
            } else {
              in = splitData.getFSDataInputStream();
            }
            
            // Now use in
            // ...
            
          

          So, having the open api which returns something like StreamOrCached will be useful as sketched above.

          Open to other ideas, but hopefully I put across what I'm looking for.

          Thoughts?

          Show
          Arun C Murthy added a comment - 1. The main reason we added auto-caching of new files was actually for Hive. My understanding is that Hive users can drop new files into a Hive partition directory without notifying the Hive metastore, e.g. via the fs shell. Usually partitions in Hive are new directories. So every 5 or 10 or 15 mins a new directory is added along with new data. Hence, the ability to automatically cache new files seems redundant. 2. We were planning on extending the existing getFileBlockLocations API (which takes a Path, offset, and length) to also indicate which replicas of the returned blocks are cached. This should satisfy the needs of framework schedulers like MR or Impala. Andrew Wang Agree that the enhancement to getFileBlockLocations suffices for the scheduler. However, at read time it will be very useful to get an indicator on whether it's cached or not during open. The RecordReader needs this API to decide whether to do stream-based reads (when data isn't cached in RAM) or mmap the file (when it's cached). It would be unfortunate to have to do another call to getFileBlockLocations to validate during read time. For e.g. SequenceFileRecordReader.initialize would look something like: SequenceFileRecordReader.java public void initialize(InputSplit split, TaskAttemptContext context ) throws IOException, InterruptedException { // ... StreamOrCached splitData = split.getPath().open(fileSplit.getStart(), fileSplit.getLength(); InputStream in = null ; if (in.isCached()) { in = new ByteBufferInputStream(splitData.getByteBuffer()); } else { in = splitData.getFSDataInputStream(); } // Now use in // ... So, having the open api which returns something like StreamOrCached will be useful as sketched above. Open to other ideas, but hopefully I put across what I'm looking for. Thoughts?
          Hide
          Arun C Murthy added a comment -

          Tying in YARN would definitely be great. There's half a hope that we can jump right from a prototype naive scheme to using YARN directly ...

          I'm happy to help to get that done, let's discuss more.

          Agree that having right abstractions is important.

          Show
          Arun C Murthy added a comment - Tying in YARN would definitely be great. There's half a hope that we can jump right from a prototype naive scheme to using YARN directly ... I'm happy to help to get that done, let's discuss more. Agree that having right abstractions is important.
          Hide
          Andrew Wang added a comment -

          Hi Arun,

          On the read path comments, it might be elucidating to check out the zero-copy read API that Colin's working on at HDFS-4953. The idea is that clients always use the zero copy cursor to do reads, which behind the scenes will do an mmap'd read if the block is cached, or a normal copying read if the block is on disk or remote. It allows an isCached-type check via not setting a fallback buffer for copying reads. This will cause the cursor to throw an exception on read if the block is not cached. Finally, there's also a parameter for enabling short reads, which comes into play when a read spans block files.

          On YARN integration, I'd like to revisit that a little ways down the road since we're focusing on getting a basic prototype out. If you want to get started on it now, it'd be helpful if you could review the current RM plan in the doc, and sketch out how a YARN-based architecture would look.

          Show
          Andrew Wang added a comment - Hi Arun, On the read path comments, it might be elucidating to check out the zero-copy read API that Colin's working on at HDFS-4953 . The idea is that clients always use the zero copy cursor to do reads, which behind the scenes will do an mmap'd read if the block is cached, or a normal copying read if the block is on disk or remote. It allows an isCached -type check via not setting a fallback buffer for copying reads. This will cause the cursor to throw an exception on read if the block is not cached. Finally, there's also a parameter for enabling short reads, which comes into play when a read spans block files. On YARN integration, I'd like to revisit that a little ways down the road since we're focusing on getting a basic prototype out. If you want to get started on it now, it'd be helpful if you could review the current RM plan in the doc, and sketch out how a YARN-based architecture would look.
          Hide
          Stephen Chu added a comment -

          Attaching the test plan for this feature (caching-testplan.pdf).

          Show
          Stephen Chu added a comment - Attaching the test plan for this feature (caching-testplan.pdf).
          Hide
          Andrew Wang added a comment -

          Consolidated patch attached to get a Jenkins run.

          Show
          Andrew Wang added a comment - Consolidated patch attached to get a Jenkins run.
          Hide
          Colin Patrick McCabe added a comment -

          updated design doc.

          Revisions:

          • change future tense to present tense in some cases.
          • grammar corrections
          • update to reflect the fact that caching information is stored in LocatedBlocks rather than BlockLocation
          • move "cache expiry" feature to future work
          • remove part about pools being in a configuration file (they are stored in the edit log)
          • rework API documentation to match current API
          Show
          Colin Patrick McCabe added a comment - updated design doc. Revisions: change future tense to present tense in some cases. grammar corrections update to reflect the fact that caching information is stored in LocatedBlocks rather than BlockLocation move "cache expiry" feature to future work remove part about pools being in a configuration file (they are stored in the edit log) rework API documentation to match current API
          Hide
          Hadoop QA added a comment -

          -1 overall. Here are the results of testing the latest attachment
          http://issues.apache.org/jira/secure/attachment/12610186/caching-design-doc-2013-10-24.pdf
          against trunk revision .

          -1 patch. The patch command could not apply the patch.

          Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5272//console

          This message is automatically generated.

          Show
          Hadoop QA added a comment - -1 overall . Here are the results of testing the latest attachment http://issues.apache.org/jira/secure/attachment/12610186/caching-design-doc-2013-10-24.pdf against trunk revision . -1 patch . The patch command could not apply the patch. Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5272//console This message is automatically generated.
          Hide
          Chris Nauroth added a comment -

          Thank you, Colin and Stephen. The design doc and test plan LGTM.

          Show
          Chris Nauroth added a comment - Thank you, Colin and Stephen. The design doc and test plan LGTM.
          Hide
          Hadoop QA added a comment -

          -1 overall. Here are the results of testing the latest attachment
          http://issues.apache.org/jira/secure/attachment/12610166/HDFS-4949-consolidated.patch
          against trunk revision .

          +1 @author. The patch does not contain any @author tags.

          +1 tests included. The patch appears to include 29 new or modified test files.

          -1 javac. The applied patch generated 1551 javac compiler warnings (more than the trunk's current 1548 warnings).

          -1 javadoc. The javadoc tool appears to have generated 5 warning messages.

          +1 eclipse:eclipse. The patch built with eclipse:eclipse.

          -1 findbugs. The patch appears to introduce 8 new Findbugs (version 1.3.9) warnings.

          -1 release audit. The applied patch generated 1 release audit warnings.

          -1 core tests. The patch failed these unit tests in hadoop-common-project/hadoop-common hadoop-hdfs-project/hadoop-hdfs:

          org.apache.hadoop.hdfs.web.TestJsonUtil
          org.apache.hadoop.hdfs.tools.offlineEditsViewer.TestOfflineEditsViewer

          +1 contrib tests. The patch passed contrib unit tests.

          Test results: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//testReport/
          Release audit warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/patchReleaseAuditProblems.txt
          Findbugs warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/newPatchFindbugsWarningshadoop-hdfs.html
          Javac warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/diffJavacWarnings.txt
          Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//console

          This message is automatically generated.

          Show
          Hadoop QA added a comment - -1 overall . Here are the results of testing the latest attachment http://issues.apache.org/jira/secure/attachment/12610166/HDFS-4949-consolidated.patch against trunk revision . +1 @author . The patch does not contain any @author tags. +1 tests included . The patch appears to include 29 new or modified test files. -1 javac . The applied patch generated 1551 javac compiler warnings (more than the trunk's current 1548 warnings). -1 javadoc . The javadoc tool appears to have generated 5 warning messages. +1 eclipse:eclipse . The patch built with eclipse:eclipse. -1 findbugs . The patch appears to introduce 8 new Findbugs (version 1.3.9) warnings. -1 release audit . The applied patch generated 1 release audit warnings. -1 core tests . The patch failed these unit tests in hadoop-common-project/hadoop-common hadoop-hdfs-project/hadoop-hdfs: org.apache.hadoop.hdfs.web.TestJsonUtil org.apache.hadoop.hdfs.tools.offlineEditsViewer.TestOfflineEditsViewer +1 contrib tests . The patch passed contrib unit tests. Test results: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//testReport/ Release audit warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/patchReleaseAuditProblems.txt Findbugs warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/newPatchFindbugsWarningshadoop-hdfs.html Javac warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//artifact/trunk/patchprocess/diffJavacWarnings.txt Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5270//console This message is automatically generated.
          Hide
          Andrew Wang added a comment -

          New patch attached. The RAT error is spurious due to the CHANGES-HDFS-4949.txt file. I also want to fix the edits unit test after we merge, since historically checking in the new binary file has been tricky to get right via patch. We've gotten clean unit test runs on upstream Jenkins, so I have confidence that it's correct. Finally, the javac warnings are also intentional, related to using the internal unmap APIs.

          Show
          Andrew Wang added a comment - New patch attached. The RAT error is spurious due to the CHANGES- HDFS-4949 .txt file. I also want to fix the edits unit test after we merge, since historically checking in the new binary file has been tricky to get right via patch. We've gotten clean unit test runs on upstream Jenkins, so I have confidence that it's correct. Finally, the javac warnings are also intentional, related to using the internal unmap APIs.
          Hide
          Hadoop QA added a comment -

          -1 overall. Here are the results of testing the latest attachment
          http://issues.apache.org/jira/secure/attachment/12610221/HDFS-4949-consolidated.patch
          against trunk revision .

          +1 @author. The patch does not contain any @author tags.

          +1 tests included. The patch appears to include 30 new or modified test files.

          -1 javac. The applied patch generated 1551 javac compiler warnings (more than the trunk's current 1548 warnings).

          +1 javadoc. The javadoc tool did not generate any warning messages.

          +1 eclipse:eclipse. The patch built with eclipse:eclipse.

          +1 findbugs. The patch does not introduce any new Findbugs (version 1.3.9) warnings.

          -1 release audit. The applied patch generated 1 release audit warnings.

          -1 core tests. The patch failed these unit tests in hadoop-common-project/hadoop-common hadoop-hdfs-project/hadoop-hdfs:

          org.apache.hadoop.hdfs.tools.offlineEditsViewer.TestOfflineEditsViewer

          +1 contrib tests. The patch passed contrib unit tests.

          Test results: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//testReport/
          Release audit warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//artifact/trunk/patchprocess/patchReleaseAuditProblems.txt
          Javac warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//artifact/trunk/patchprocess/diffJavacWarnings.txt
          Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//console

          This message is automatically generated.

          Show
          Hadoop QA added a comment - -1 overall . Here are the results of testing the latest attachment http://issues.apache.org/jira/secure/attachment/12610221/HDFS-4949-consolidated.patch against trunk revision . +1 @author . The patch does not contain any @author tags. +1 tests included . The patch appears to include 30 new or modified test files. -1 javac . The applied patch generated 1551 javac compiler warnings (more than the trunk's current 1548 warnings). +1 javadoc . The javadoc tool did not generate any warning messages. +1 eclipse:eclipse . The patch built with eclipse:eclipse. +1 findbugs . The patch does not introduce any new Findbugs (version 1.3.9) warnings. -1 release audit . The applied patch generated 1 release audit warnings. -1 core tests . The patch failed these unit tests in hadoop-common-project/hadoop-common hadoop-hdfs-project/hadoop-hdfs: org.apache.hadoop.hdfs.tools.offlineEditsViewer.TestOfflineEditsViewer +1 contrib tests . The patch passed contrib unit tests. Test results: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//testReport/ Release audit warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//artifact/trunk/patchprocess/patchReleaseAuditProblems.txt Javac warnings: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//artifact/trunk/patchprocess/diffJavacWarnings.txt Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5273//console This message is automatically generated.
          Hide
          Suresh Srinivas added a comment -

          Given that the merge vote thread has been started, can someone post details about what functionality from original design has been completed and what is pending? Looks like the current functionality does not cover quota management. Any other features pending?

          Show
          Suresh Srinivas added a comment - Given that the merge vote thread has been started, can someone post details about what functionality from original design has been completed and what is pending? Looks like the current functionality does not cover quota management. Any other features pending?
          Hide
          Chris Nauroth added a comment -

          Here is a list of items discussed in the design doc to be completed later, with corresponding jira if it exists:

          • quota enforcement - need to file jira?
          • cache expiry based on TTL - need to file jira?
          • incremental cache reports - HDFS-5092
          • metrics - HDFS-5320
          Show
          Chris Nauroth added a comment - Here is a list of items discussed in the design doc to be completed later, with corresponding jira if it exists: quota enforcement - need to file jira? cache expiry based on TTL - need to file jira? incremental cache reports - HDFS-5092 metrics - HDFS-5320
          Hide
          Colin Patrick McCabe added a comment -

          quick note: The reason why TestOfflineEditsViewer failed in jenkins is that the consolidated patch didn't change the binary edit log file used by that test. It succeeds on the branch.

          incremental cache reports - HDFS-5092

          This is listed as a maybe in the design doc-- it's something that we want to evaluate before doing

          quotas, metrics, and TTL are definitely post-merge, I think.

          Show
          Colin Patrick McCabe added a comment - quick note: The reason why TestOfflineEditsViewer failed in jenkins is that the consolidated patch didn't change the binary edit log file used by that test. It succeeds on the branch. incremental cache reports - HDFS-5092 This is listed as a maybe in the design doc-- it's something that we want to evaluate before doing quotas, metrics, and TTL are definitely post-merge, I think.
          Hide
          Chris Nauroth added a comment -

          +1 for the merge. Thanks again, Andrew and Colin.

          Show
          Chris Nauroth added a comment - +1 for the merge. Thanks again, Andrew and Colin.
          Hide
          Hudson added a comment -

          SUCCESS: Integrated in Hadoop-trunk-Commit #4664 (See https://builds.apache.org/job/Hadoop-trunk-Commit/4664/)
          Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572)

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          Show
          Hudson added a comment - SUCCESS: Integrated in Hadoop-trunk-Commit #4664 (See https://builds.apache.org/job/Hadoop-trunk-Commit/4664/ ) Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572 ) /hadoop/common/trunk /hadoop/common/trunk/hadoop-common-project/hadoop-common/CHANGES.txt /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/docs /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/BatchedRemoteIterator.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ByteBufferUtil.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/HasEnhancedByteBufferAccess.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ReadOption.java 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          Hide
          Hudson added a comment -

          SUCCESS: Integrated in Hadoop-Yarn-trunk #377 (See https://builds.apache.org/job/Hadoop-Yarn-trunk/377/)
          Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572)

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          Hudson added a comment - SUCCESS: Integrated in Hadoop-Yarn-trunk #377 (See https://builds.apache.org/job/Hadoop-Yarn-trunk/377/ ) Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572 ) /hadoop/common/trunk /hadoop/common/trunk/hadoop-common-project/hadoop-common/CHANGES.txt /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/docs /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/BatchedRemoteIterator.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ByteBufferUtil.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/HasEnhancedByteBufferAccess.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ReadOption.java 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/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/fsdataset/impl/FsDatasetImpl.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/fsdataset/impl/FsVolumeImpl.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/fsdataset/impl/MappableBlock.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/metrics/DataNodeMetrics.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/datanode/metrics/FSDatasetMBean.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/CacheManager.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/CachePool.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/CachedBlock.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSDirectory.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSEditLog.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSEditLogLoader.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSEditLogOp.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSEditLogOpCodes.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSImageFormat.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSNamesystem.java 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/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/ha/TestRetryCacheWithHA.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/web/TestJsonUtil.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/editsStored /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/editsStored.xml /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/testCacheAdminConf.xml /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/testHDFSConf.xml /hadoop/common/trunk/hadoop-mapreduce-project /hadoop/common/trunk/hadoop-mapreduce-project/CHANGES.txt /hadoop/common/trunk/hadoop-mapreduce-project/conf /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/resources/mapred-default.xml
          Hide
          Hudson added a comment -

          FAILURE: Integrated in Hadoop-Hdfs-trunk #1567 (See https://builds.apache.org/job/Hadoop-Hdfs-trunk/1567/)
          Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572)

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          Show
          Hudson added a comment - FAILURE: Integrated in Hadoop-Hdfs-trunk #1567 (See https://builds.apache.org/job/Hadoop-Hdfs-trunk/1567/ ) Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572 ) /hadoop/common/trunk /hadoop/common/trunk/hadoop-common-project/hadoop-common/CHANGES.txt /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/docs /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/BatchedRemoteIterator.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ByteBufferUtil.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/HasEnhancedByteBufferAccess.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ReadOption.java 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          Hide
          Hudson added a comment -

          FAILURE: Integrated in Hadoop-Mapreduce-trunk #1593 (See https://builds.apache.org/job/Hadoop-Mapreduce-trunk/1593/)
          Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572)

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          Hudson added a comment - FAILURE: Integrated in Hadoop-Mapreduce-trunk #1593 (See https://builds.apache.org/job/Hadoop-Mapreduce-trunk/1593/ ) Merge HDFS-4949 branch back into trunk (cmccabe: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1536572 ) /hadoop/common/trunk /hadoop/common/trunk/hadoop-common-project/hadoop-common/CHANGES.txt /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/docs /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/BatchedRemoteIterator.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ByteBufferUtil.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/HasEnhancedByteBufferAccess.java /hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/fs/ReadOption.java 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/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSPermissionChecker.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/NameNode.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/NameNodeRpcServer.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/metrics/NameNodeMetrics.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/startupprogress/StepType.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/protocol/BlockIdCommand.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/protocol/DatanodeProtocol.java 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/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/fs/TestEnhancedByteBufferAccess.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/DFSTestUtil.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/LogVerificationAppender.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/TestDatanodeConfig.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/protocolPB/TestClientNamenodeProtocolServerSideTranslatorPB.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/blockmanagement/TestBlockManager.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/blockmanagement/TestCachedBlocksList.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/blockmanagement/TestOverReplicatedBlocks.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/blockmanagement/TestReplicationPolicy.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/blockmanagement/TestReplicationPolicyWithNodeGroup.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/common/TestJspHelper.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/datanode/SimulatedFSDataset.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/datanode/TestBPOfferService.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/datanode/TestBlockRecovery.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/datanode/TestFsDatasetCache.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/NNThroughputBenchmark.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/NameNodeAdapter.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/OfflineEditsViewerHelper.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/TestDeadDatanode.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/TestNamenodeRetryCache.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/TestPathBasedCacheRequests.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/server/namenode/ha/TestRetryCacheWithHA.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/java/org/apache/hadoop/hdfs/web/TestJsonUtil.java /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/editsStored /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/editsStored.xml /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/testCacheAdminConf.xml /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/test/resources/testHDFSConf.xml /hadoop/common/trunk/hadoop-mapreduce-project /hadoop/common/trunk/hadoop-mapreduce-project/CHANGES.txt /hadoop/common/trunk/hadoop-mapreduce-project/conf /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/resources/mapred-default.xml
          Hide
          Fengdong Yu added a comment -

          Vote thread has been started for a month, but HDFS-4949 branch still not merged with trunk, does that has any blockers here?

          Show
          Fengdong Yu added a comment - Vote thread has been started for a month, but HDFS-4949 branch still not merged with trunk, does that has any blockers here?
          Hide
          Chris Nauroth added a comment -

          Hi, Fengdong Yu. The merge vote passed and HDFS-4949 was merged to trunk about a month ago. For example, here you can see the CacheManager class on trunk:

          http://svn.apache.org/viewvc/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/CacheManager.java

          Show
          Chris Nauroth added a comment - Hi, Fengdong Yu . The merge vote passed and HDFS-4949 was merged to trunk about a month ago. For example, here you can see the CacheManager class on trunk: http://svn.apache.org/viewvc/hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/CacheManager.java
          Hide
          Fengdong Yu added a comment -

          Chris Nauroth, yes, I can find CacheManager in the trunk, but it's not consistent with HDFS-4949 branch.

          Does that always committed in HDFS-4949 even after merged with trunk?

          Show
          Fengdong Yu added a comment - Chris Nauroth , yes, I can find CacheManager in the trunk, but it's not consistent with HDFS-4949 branch. Does that always committed in HDFS-4949 even after merged with trunk?
          Hide
          Andrew Wang added a comment -

          Hey Fengdong Yu, since the merge, we've been committing caching-related patches just to trunk. The branch is now defunct. We're still using this JIRA for tracking ongoing subtasks though, and some JIRAs also have the "caching" label.

          Show
          Andrew Wang added a comment - Hey Fengdong Yu , since the merge, we've been committing caching-related patches just to trunk. The branch is now defunct. We're still using this JIRA for tracking ongoing subtasks though, and some JIRAs also have the "caching" label.
          Hide
          Fengdong Yu added a comment -

          Thanks, Andrew.

          Show
          Fengdong Yu added a comment - Thanks, Andrew.
          Hide
          Arun C Murthy added a comment -

          We've been discussing through a proposal where-in we can leverage YARN's resource-management and workload-management capabilities (via delegation of resources, in this case RAM to HDFS) to provide a more general cache administration in YARN-1488.

          Show
          Arun C Murthy added a comment - We've been discussing through a proposal where-in we can leverage YARN's resource-management and workload-management capabilities (via delegation of resources, in this case RAM to HDFS) to provide a more general cache administration in YARN-1488 .
          Hide
          Andrew Wang added a comment -

          Attached is a consolidated patch for branch-2. Unfortunately we left the HDFS-4949 branch fallow while development continued in trunk, but I did my best to squash all of the caching-related patches committed thus far into this mega patch. A preliminary test run of HDFS and Common looked good, but I'm running another right now on this version of the patch to verify.

          Show
          Andrew Wang added a comment - Attached is a consolidated patch for branch-2. Unfortunately we left the HDFS-4949 branch fallow while development continued in trunk, but I did my best to squash all of the caching-related patches committed thus far into this mega patch. A preliminary test run of HDFS and Common looked good, but I'm running another right now on this version of the patch to verify.
          Hide
          Hadoop QA added a comment -

          -1 overall. Here are the results of testing the latest attachment
          http://issues.apache.org/jira/secure/attachment/12624211/hdfs-4949-branch-2.patch
          against trunk revision .

          -1 patch. The patch command could not apply the patch.

          Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5930//console

          This message is automatically generated.

          Show
          Hadoop QA added a comment - -1 overall . Here are the results of testing the latest attachment http://issues.apache.org/jira/secure/attachment/12624211/hdfs-4949-branch-2.patch against trunk revision . -1 patch . The patch command could not apply the patch. Console output: https://builds.apache.org/job/PreCommit-HDFS-Build/5930//console This message is automatically generated.
          Hide
          Colin Patrick McCabe added a comment -

          branch-2 patch looks good to me; thanks Andrew

          Show
          Colin Patrick McCabe added a comment - branch-2 patch looks good to me; thanks Andrew
          Hide
          Andrew Wang added a comment -

          Thanks Colin. The branch-2 test run I did with this also came back clean, so I think it's good to go. Will commit shortly.

          Show
          Andrew Wang added a comment - Thanks Colin. The branch-2 test run I did with this also came back clean, so I think it's good to go. Will commit shortly.
          Hide
          Andrew Wang added a comment -

          I've committed this to branch-2 and fixed up the CHANGES.txt in branch-2 and trunk accordingly. It might finally be time to resolve this parent issue, and punt all remaining subtasks out into their own standalone issues.

          Show
          Andrew Wang added a comment - I've committed this to branch-2 and fixed up the CHANGES.txt in branch-2 and trunk accordingly. It might finally be time to resolve this parent issue, and punt all remaining subtasks out into their own standalone issues.
          Hide
          Andrew Wang added a comment -

          I went through and resolved or pushed out all remaining subtasks. With the code in branch-2, we can resolve this parent issue. Thanks for all the contributions from everyone involved!

          Show
          Andrew Wang added a comment - I went through and resolved or pushed out all remaining subtasks. With the code in branch-2, we can resolve this parent issue. Thanks for all the contributions from everyone involved!
          Hide
          Hudson added a comment -

          SUCCESS: Integrated in Hadoop-trunk-Commit #5035 (See https://builds.apache.org/job/Hadoop-trunk-Commit/5035/)
          Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528)

          • /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Show
          Hudson added a comment - SUCCESS: Integrated in Hadoop-trunk-Commit #5035 (See https://builds.apache.org/job/Hadoop-trunk-Commit/5035/ ) Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528 ) /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Hide
          Hudson added a comment -

          FAILURE: Integrated in Hadoop-Yarn-trunk #461 (See https://builds.apache.org/job/Hadoop-Yarn-trunk/461/)
          Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528)

          • /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Show
          Hudson added a comment - FAILURE: Integrated in Hadoop-Yarn-trunk #461 (See https://builds.apache.org/job/Hadoop-Yarn-trunk/461/ ) Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528 ) /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Hide
          Hudson added a comment -

          FAILURE: Integrated in Hadoop-Mapreduce-trunk #1678 (See https://builds.apache.org/job/Hadoop-Mapreduce-trunk/1678/)
          Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528)

          • /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Show
          Hudson added a comment - FAILURE: Integrated in Hadoop-Mapreduce-trunk #1678 (See https://builds.apache.org/job/Hadoop-Mapreduce-trunk/1678/ ) Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528 ) /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Hide
          Hudson added a comment -

          SUCCESS: Integrated in Hadoop-Hdfs-trunk #1653 (See https://builds.apache.org/job/Hadoop-Hdfs-trunk/1653/)
          Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528)

          • /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
          Show
          Hudson added a comment - SUCCESS: Integrated in Hadoop-Hdfs-trunk #1653 (See https://builds.apache.org/job/Hadoop-Hdfs-trunk/1653/ ) Move HDFS-4949 subtasks in CHANGES.txt to a new section under 2.4.0 release. (wang: http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1560528 ) /hadoop/common/trunk/hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt

            People

            • Assignee:
              Andrew Wang
              Reporter:
              Andrew Wang
            • Votes:
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              Watchers:
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              Dates

              • Created:
                Updated:
                Resolved:

                Development