[HADOOP-15913] xml parsing error in a heavily multi-threaded environment - ASF JIRA

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Details

Type: Bug
Status: Open
Priority: Critical
Resolution: Unresolved
Affects Version/s: 2.7.3
Fix Version/s: None
Component/s: common
Labels:
None

Description

We met this problem in a production environment, the stack trace like this:

ERROR org.apache.hadoop.hive.ql.exec.Task: Ended Job = job_1541600895081_0580 with exception 'java.lang.NullPointerException(Inflater has been closed)'
java.lang.NullPointerException: Inflater has been closed
        at java.util.zip.Inflater.ensureOpen(Inflater.java:389)
        at java.util.zip.Inflater.inflate(Inflater.java:257)
        at java.util.zip.InflaterInputStream.read(InflaterInputStream.java:152)
        at java.io.FilterInputStream.read(FilterInputStream.java:133)
        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:283)
        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:325)
        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:177)
        at java.io.InputStreamReader.read(InputStreamReader.java:184)
        at java.io.BufferedReader.fill(BufferedReader.java:154)
        at java.io.BufferedReader.readLine(BufferedReader.java:317)
        at java.io.BufferedReader.readLine(BufferedReader.java:382)
        at javax.xml.parsers.FactoryFinder.findJarServiceProvider(FactoryFinder.java:319)
        at javax.xml.parsers.FactoryFinder.find(FactoryFinder.java:255)
        at javax.xml.parsers.DocumentBuilderFactory.newInstance(DocumentBuilderFactory.java:121)
        at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2524)
        at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2501)
        at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2407)
        at org.apache.hadoop.conf.Configuration.get(Configuration.java:983)
        at org.apache.hadoop.mapred.JobConf.checkAndWarnDeprecation(JobConf.java:2007)
        at org.apache.hadoop.mapred.JobConf.<init>(JobConf.java:479)
        at org.apache.hadoop.mapred.JobConf.<init>(JobConf.java:469)
        at org.apache.hadoop.mapreduce.Cluster.getJob(Cluster.java:188)
        at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:601)
        at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:599)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:415)
        at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
        at org.apache.hadoop.mapred.JobClient.getJobUsingCluster(JobClient.java:599)
        at org.apache.hadoop.mapred.JobClient.getJobInner(JobClient.java:609)
        at org.apache.hadoop.mapred.JobClient.getJob(JobClient.java:639)
        at org.apache.hadoop.hive.ql.exec.mr.HadoopJobExecHelper.progress(HadoopJobExecHelper.java:294)
        at org.apache.hadoop.hive.ql.exec.mr.HadoopJobExecHelper.progress(HadoopJobExecHelper.java:558)
        at org.apache.hadoop.hive.ql.exec.mr.ExecDriver.execute(ExecDriver.java:457)
        at org.apache.hadoop.hive.ql.exec.mr.MapRedTask.execute(MapRedTask.java:141)
        at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:197)

and can reproduce it in our test environment by steps below:
1. set configs:

hive.server2.async.exec.threads  = 50
hive.server2.async.exec.wait.queue.size = 100

2. open 4 beeline terminates in 4 different nodes.
3. create 30 queries in each beeline terminate. Each query include "add jar xxx.jar" like this:

add jar mykeytest-1.0-SNAPSHOT.jar;
create temporary function ups as 'com.xxx.manager.GetCommentNameOrId';
insert into test partition(tjrq = ${my_no}, ywtx = '${my_no2}' )
select  dt.d_year as i_brand
       ,item.i_brand_id as i_item_sk
       ,ups(item.i_brand) as i_product_name
       ,sum(ss_ext_sales_price) as i_category_id
 from  date_dim dt
      ,store_sales
      ,item
 where dt.d_date_sk = store_sales.ss_sold_date_sk
   and store_sales.ss_item_sk = item.i_item_sk
   and item.i_manufact_id = 436
   and dt.d_moy=12
 group by dt.d_year
      ,item.i_brand
      ,item.i_brand_id
 order by dt.d_year

and all these 120 queries connect to one hiveserver2

Run all the query concurrently, and will see the stack trace abover in hiveserver2 log