Details
-
Bug
-
Status: Resolved
-
Critical
-
Resolution: Cannot Reproduce
-
None
-
None
-
None
-
None
-
Hadoop-0.18.0, 7 node Linux grid (6 DataNodes, 1 master node)
Hadoop-0.18.0, 20 EC2 Linux grid (19 DataNodes, 1 master node)
Description
9/27 update: uploaded the logs, with hopefully all the bits that should be examined. If other things are needed, just let me know. Note that all the paths refer to 0.18.1. This is still an 18.0 installation using the 18.0 core jar, just installed to a non-standard location.
9/26 update: we have successfully reproduced this using Hadoop 0.18 as well. The problem happens on both our own network infrastructure as well as on an Amazon EC2 cluster running CentOS5 images. I'll be attaching the logs Raghu asked for shortly.
A job that used to run correctly on our grid (in 0.15.0) now fails. The failure occurs after the map phase is complete, and about 2/3rds of the way through the reduce phase. This job is processing a modest amount of input data (approximately 220G)
When the error occurs the nodes hosting DataNodes have literally thousands of open socket connections on them. The DataNode instances are holding large amounts of memory. Sometimes the DataNodes crash or exit, other times they continue to run.
The error which gets kicked out from the application perspective is:
08/05/27 11:30:08 INFO mapred.JobClient: map 100% reduce 89%
08/05/27 11:30:41 INFO mapred.JobClient: map 100% reduce 90%
08/05/27 11:32:45 INFO mapred.JobClient: map 100% reduce 86%
08/05/27 11:32:45 INFO mapred.JobClient: Task Id :
task_200805271056_0001_r_000007_0, Status : FAILED
java.io.IOException: Could not get block locations. Aborting...
at org.apache.hadoop.dfs.DFSClient$DFSOutputStream.processDatanode
Error(DFSClient.java:1832)
at
org.apache.hadoop.dfs.DFSClient$DFSOutputStream.access$1100(DFSClient.java:1487)
at
org.apache.hadoop.dfs.DFSClient$DFSOutputStream$DataStreamer.run(DFSClient.java:1579)
I then discovered that 1 or more DataNode instances on the slave nodes
are down (we run 1 DataNode instance per machine). The cause for at
least some of the DataNode failures is a JVM internal error that gets
raised due to a complete out-of-memory scenario (on a 4G, 4-way machine).
Watching the DataNodes run, I can see them consuming more and more
memory. For those failures for which there is a JVM traceback, I see (in
part...NOTE 0.16.4 TRACEBACK):
#
- java.lang.OutOfMemoryError: requested 16 bytes for CHeapObj-new. Out
of swap space?
# - Internal Error (414C4C4F434154494F4E0E494E4C494E450E4850500017),
pid=4246, tid=2283883408
# - Java VM: Java HotSpot(TM) Server VM (1.6.0_02-b05 mixed mode)
- If you would like to submit a bug report, please visit:
- http://java.sun.com/webapps/bugreport/crash.jsp
#-
-
-
-
-
-
-
-
-
-
-
-
-
- T H R E A D ---------------
Current thread (0x8a942000): JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@3f4f44" daemon [_thread_in_Java, id=15064]
Stack: [0x881c4000,0x88215000), sp=0x882139e0, free space=318k
Native frames: (J=compiled Java code, j=interpreted, Vv=VM code,
C=native code)
V [libjvm.so+0x53b707]
V [libjvm.so+0x225fe1]
V [libjvm.so+0x16fdc5]
V [libjvm.so+0x22aef3]
Java frames: (J=compiled Java code, j=interpreted, Vv=VM code)
v blob 0xf4f235a7
J java.io.DataInputStream.readInt()I
j
org.apache.hadoop.dfs.DataNode$BlockReceiver.receiveBlock(Ljava/io/DataOutputStream;Ljava/io/DataInputStream;Ljava/io/DataOutputStream;Ljava/lang/String;Lorg/a
pache/hadoop/dfs/DataNode$Throttler;I)V+126
j
org.apache.hadoop.dfs.DataNode$DataXceiver.writeBlock(Ljava/io/DataInputStream;)V+746
j org.apache.hadoop.dfs.DataNode$DataXceiver.run()V+174
j java.lang.Thread.run()V+11
v ~StubRoutines::call_stub - P R O C E S S ---------------
Java Threads: ( => current thread )
0x0ae3f400 JavaThread "process reaper" daemon [_thread_blocked,
id=26870]
0x852e6000 JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@e5dce1" daemon [_thread_in_vm, id=26869]
0x08a1cc00 JavaThread "PacketResponder 0 for Block
blk_-6186975972786687394" daemon [_thread_blocked, id=26769]
0x852e5000 JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@c40bf8" daemon [_thread_in_native, id=26768]
0x0956e000 JavaThread "PacketResponder 0 for Block
blk_-2322514873363546651" daemon [_thread_blocked, id=26767]
0x852e4400 JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@1ca61f9" daemon [_thread_in_native, id=26766]
0x09d3a400 JavaThread "PacketResponder 0 for Block
blk_8926941945313450801" daemon [_thread_blocked, id=26764]
0x852e3c00 JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@1e186d9" daemon [_thread_in_native, id=26763]
0x0953d000 JavaThread "PacketResponder 0 for Block
blk_4785883052769066976" daemon [_thread_blocked, id=26762]
0xb13a5c00 JavaThread
"org.apache.hadoop.dfs.DataNode$DataXceiver@13d62aa" daemon [_thread_in_native, id=26761]
- T H R E A D ---------------
-
-
-
-
-
-
-
-
-
-
-
-
-
The interesting part here is that if I count the number of JavaThreads
running org.apache.hadoop.dfs.DataNode I see 4,538 
in the
traceback. The number of threads was surprising.
Other DataNodes just exit without panicking the JVM. In either failure
mode, the last few lines of the DataNode log file is apparently
innocuous:
2008-05-27 11:31:47,663 INFO org.apache.hadoop.dfs.DataNode: Datanode 2
got response for connect ack from downstream datanode with
firstbadlink as
2008-05-27 11:31:47,663 INFO org.apache.hadoop.dfs.DataNode: Datanode 2
forwarding connect ack to upstream firstbadlink is
2008-05-27 11:31:48,268 INFO org.apache.hadoop.dfs.DataNode: Receiving
block blk_-2241766430103062484 src: /10.2.14.10:33626 dest:
/10.2.14.10:50010
2008-05-27 11:31:48,740 INFO org.apache.hadoop.dfs.DataNode: Receiving
block blk_313239508245918539 src: /10.2.14.24:37836 dest:
/10.2.14.24:50010
2008-05-27 11:31:48,740 INFO org.apache.hadoop.dfs.DataNode: Datanode 0
forwarding connect ack to upstream firstbadlink is
2008-05-27 11:31:49,044 INFO org.apache.hadoop.dfs.DataNode: Receiving
block blk_1684581399908730353 src: /10.2.14.16:51605 dest:
/10.2.14.16:50010
2008-05-27 11:31:49,044 INFO org.apache.hadoop.dfs.DataNode: Datanode 0
forwarding connect ack to upstream firstbadlink is
2008-05-27 11:31:49,509 INFO org.apache.hadoop.dfs.DataNode: Receiving
block blk_2493969670086107736 src: /10.2.14.18:47557 dest:
/10.2.14.18:50010
2008-05-27 11:31:49,513 INFO org.apache.hadoop.dfs.DataNode: Datanode 1
got response for connect ack from downstream datanode with
firstbadlink as
2008-05-27 11:31:49,513 INFO org.apache.hadoop.dfs.DataNode: Datanode 1
forwarding connect ack to upstream firstbadlink is
Finally, the task-level output (in userlogs) doesn't reveal much
either:
2008-05-27 11:38:30,724 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 Need 34 map output(s)
2008-05-27 11:38:30,753 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 done copying
task_200805271056_0001_m_001976_0 output from worker9.
2008-05-27 11:38:31,727 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1: Got 0 new map-outputs & 0 obsolete
map-outputs from tasktracker and 0 map-outputs from previous failures
2008-05-27 11:38:31,727 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 Got 33 known map output location(s);
scheduling...
2008-05-27 11:38:31,727 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 Scheduled 1 of 33 known outputs (0 slow
hosts and 32 dup hosts)
2008-05-27 11:38:31,727 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 Copying task_200805271056_0001_m_001248_0
output from worker8.
2008-05-27 11:38:31,727 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 Need 33 map output(s)
2008-05-27 11:38:31,752 INFO org.apache.hadoop.mapred.ReduceTask:
task_200805271056_0001_r_000007_1 done copying
task_200805271056_0001_m_001248_0 output from worker8.