Troubleshooting |

1. Metastore fails to find a MySQL connector jar file in the classpath with `ClassNotFoundException` (on Kubernetes).

2020-07-18T04:03:14,856 ERROR [main] tools.HiveSchemaHelper: Unable to find driver class
java.lang.ClassNotFoundException: com.mysql.jdbc.Driver

The classpath of Metastore includes the directories /opt/mr3-run/lib and /opt/mr3-run/host-lib inside the Metastore Pod, and the user can place a MySQL connector jar file in one of these two directories in three different ways.

When building a Docker image, set HIVE_MYSQL_DRIVER in env.sh (not Kubernetes/env.sh) to the path of the jar file. Then the jar file is found in the directory /opt/mr3-run/lib inside the Metastore Pod.
```
bash-4.2$ ls /opt/mr3-run/lib
mysql-connector-java-5.1.49.jar
```
In this case, the user should comment out the following lines in kubernetes/yaml/metastore.yaml so that the directory /opt/mr3-run/lib is not overriden by a subdirectory in the PersistentVolume.
```
      # - name: work-dir-volume
      #   mountPath: /opt/mr3-run/lib
      #   subPath: lib
```
With Helm, the user should set metastore.mountLib to false in kubernetes/helm/hive/values.yaml.
```
metastore:
  mountLib: false
```
If the Docker image is not built with the jar file, the user can copy it to the subdirectory lib in the PersistentVolume and use PersistentVolumeClaim work-dir-volume in kubernetes/yaml/metastore.yaml. Then the jar file is mounted in the directory /opt/mr3-run/lib inside the Metastore Pod. See Copying a MySQL connector jar file to EFS in Creating a PersistentVolume using EFS for examples.
```
    - name: work-dir-volume
      mountPath: /opt/mr3-run/lib
      subPath: lib
```
With Helm, the user should set metastore.mountLib to true in kubernetes/helm/hive/values.yaml.
```
metastore:
  mountLib: true
```
If the Docker image is not built with the jar file and a PersistentVolume is not available (e.g., when using S3 instead of EFS on Amazon EKS), the user can mount it in the directory /opt/mr3-run/host-lib using a hostPath volume. See Downloading a MySQL connector in Creating an EKS cluster for an example.

With Helm, kubernetes/helm/hive/values.yaml should set metastore.hostLib to true and set metastore.hostLibDir to a common local directory containing the jar file on all worker nodes.
```
hostLib: true
hostLibDir: "/home/ec2-user/lib"
```

2. When running a query, ContainerWorker Pods never get launched and Beeline gets stuck.

Try adjusting the resource for DAGAppMaster and ContainerWorker Pods. In kubernetes/conf/mr3-site.xml, the user can adjust the resource for the DAGAppMaster Pod.

<property>
  <name>mr3.am.resource.memory.mb</name>
  <value>16384</value>
</property>

<property>
  <name>mr3.am.resource.cpu.cores</name>
  <value>2</value>
</property>

In kubernetes/conf/hive-site.xml, the user can adjust the resource for ContainerWorker Pods (assuming that the configuration key hive.mr3.containergroup.scheme is set to all-in-one).

<property>
  <name>hive.mr3.map.task.memory.mb</name>
  <value>8192</value>
</property>

<property>
  <name>hive.mr3.map.task.vcores</name>
  <value>1</value>
</property>

<property>
  <name>hive.mr3.reduce.task.memory.mb</name>
  <value>8192</value>
</property>

<property>
  <name>hive.mr3.reduce.task.vcores</name>
  <value>1</value>
</property>

<property>
  <name>hive.mr3.all-in-one.containergroup.memory.mb</name>
  <value>16384</value>
</property>

<property>
  <name>hive.mr3.all-in-one.containergroup.vcores</name>
  <value>2</value>
</property>

3. A query fails with a message `No space available in any of the local directories` (on Kubernetes).

A query may fail with the following error from Beeline:

ERROR : Terminating unsuccessfully: Vertex failed, vertex_2134_0000_1_01, Some(Task unsuccessful: Map 1, task_2134_0000_1_01_000000, java.lang.RuntimeException: org.apache.hadoop.util.DiskChecker$DiskErrorException: No space available in any of the local directories.
  at org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:370)
...
Caused by: org.apache.hadoop.util.DiskChecker$DiskErrorException: No space available in any of the local directories.

In such a case, check if the configuration key mr3.k8s.pod.worker.hostpaths in kubernetes/conf/mr3-site.xml is properly set, e.g.:

<property>
  <name>mr3.k8s.pod.worker.hostpaths</name>
  <value>/data1/k8s,/data2/k8s,/data3/k8s,/data4/k8s,/data5/k8s,/data6/k8s</value>
</property>

In addition, check if the directories listed in mr3.k8s.pod.worker.hostpaths are writable to the user running Pods.

4. A query accessing S3 fails with `SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool`

A query accessing S3 may fail with an error message SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool. This can happen in DAGAppMaster when running InputInitializer, in which case the Beeline and the DAGAppMaster Pod generate such errors as:

### from Beeline 
ERROR : FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.tez.TezTask. Terminating unsuccessfully: Vertex failed, vertex_22169_0000_1_02, Some(RootInput web_sales failed on Vertex Map 1: com.datamonad.mr3.api.common.AMInputInitializerException: web_sales)Map 1            1 task           2922266 milliseconds: Failed

### from the DAGAppMaster Pod
Caused by: java.lang.RuntimeException: ORC split generation failed with exception: java.io.InterruptedIOException: Failed to open s3a://hivemr3-partitioned-2-orc/web_sales/ws_sold_date_sk=2451932/000001_0 at 14083 on s3a://hivemr3-partitioned-2-orc/web_sales/ws_sold_date_sk=2451932/000001_0: com.amazonaws.SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool

This can also happen in ContainerWorkers, in which case ContainerWorker Pods generate such errors as:

...... com.amazonaws.SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool
at org.apache.hadoop.hive.ql.exec.FileSinkOperator$FSPaths.closeWriters(FileSinkOperator.java:202) ~[hive-exec-3.1.2.jar:3.1.2]
at org.apache.hadoop.hive.ql.exec.FileSinkOperator.closeOp(FileSinkOperator.java:1276) ~[hive-exec-3.1.2.jar:3.1.2]
...
...... com.amazonaws.SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool
at org.apache.hadoop.fs.s3a.S3AUtils.translateInterruptedException(S3AUtils.java:340) ~[hadoop-aws-3.1.2.jar:?]
...
Caused by: com.amazonaws.SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool

Depending on the settings for S3 buckets and the properties of datasets, the user may have to change the values for the following configuration keys in kubernetes/conf/core-site.xml.

increase the value for fs.s3a.connection.maximum (e.g., to 2000 or higher)
increase the value for fs.s3a.threads.max
increase the value for fs.s3a.threads.core
set fs.s3a.blocking.executor.enabled to false
set fs.s3a.connection.ssl.enabled to false

For more details, see Basic Performance Tuning.

5. A query accessing S3 makes no progress because Map vertexes get stuck in the state of `Initializing`.

If DAGAppMaster fails to resolve host names, the execution of a query may get stuck in the following state: hivek8s.am.stuck In such a case, check if the configuration key mr3.k8s.host.aliases is set properly in kubernetes/conf/mr3-site.xml. For example, if the user sets the environment variable HIVE_DATABASE_HOST in env.sh to the host name (instead of the address) of the MySQL server, its address should be specified in mr3.k8s.host.aliases.

HIVE_DATABASE_HOST=orange0

<property>
  <name>mr3.k8s.host.aliases</name>
  <value>orange0=11.11.11.11</value>
</property>

Internally the class AmazonS3Client (running inside InputInitializer of MR3) throws an exception java.net.UnknownHostException, which, however, is swallowed and never propagated to DAGAppMaster. As a consequence, no error is reported to Beeline and the query gets stuck.

6. DAGAppMaster Pod does not start because `mr3-conf.properties` does not exist.

MR3 generates a property file mr3-conf.properties from ConfigMap mr3conf-configmap-master and mounts it inside DAGAppMaster Pod. If DAGAppMaster Pod fails with the following message, it means that either ConfigMap mr3conf-configmap-master is corrupt or mr3-conf.properties has not been generated.

2020-05-15T10:35:10,255 ERROR [main] DAGAppMaster: Error in starting DAGAppMasterjava.lang.IllegalArgumentException: requirement failed: Properties file mr3-conf.properties does not exist

In such a case, try again after manually deleting ConfigMap mr3conf-configmap-master so that Hive on MR3 on Kubernetes can start without a ConfigMap of the same name.

7. Metastore fails with `Version information not found in metastore`

The following error occurs if the MySQL database for Metastore has not been initialized.

MetaException(message:Version information not found in metastore. )
...
Caused by: MetaException(message:Version information not found in metastore. )
  at org.apache.hadoop.hive.metastore.ObjectStore.checkSchema(ObjectStore.java:7564)
...

The user can initialize schema when starting Metastore by updating kubernetes/yaml/metastore.yaml as follows:

        args: ["start", "--init-schema"]

For more details, see Running Metastore.

8. HiveServer2 repeatedly prints an error message `server.TThreadPoolServer: Error occurred during processing of message`.

HiveServer2 may repeatedly print the same error message at a regular interval such as:

2020-08-13T05:28:47,351 ERROR [HiveServer2-Handler-Pool: Thread-27] server.TThreadPoolServer: Error occurred during processing of message.
java.lang.RuntimeException: org.apache.thrift.transport.TSaslTransportException: No data or no sasl data in the stream
	at org.apache.thrift.transport.TSaslServerTransport$Factory.getTransport(TSaslServerTransport.java:219) ~[hive-exec-3.1.2.jar:3.1.2]
	at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:269) ~[hive-exec-3.1.2.jar:3.1.2]
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) ~[?:1.8.0_252]
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ~[?:1.8.0_252]
	at java.lang.Thread.run(Thread.java:748) [?:1.8.0_252]
Caused by: org.apache.thrift.transport.TSaslTransportException: No data or no sasl data in the stream
...

2020-08-13T04:51:23,697 ERROR [HiveServer2-Handler-Pool: Thread-27] server.TThreadPoolServer: Error occurred during processing of message.
java.lang.RuntimeException: org.apache.thrift.transport.TTransportException: javax.net.ssl.SSLHandshakeException: Remote host closed connection during handshake
	at org.apache.thrift.transport.TSaslServerTransport$Factory.getTransport(TSaslServerTransport.java:219) ~[hive-exec-3.1.2.jar:3.1.2]
	at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:269) ~[hive-exec-3.1.2.jar:3.1.2]
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) ~[?:1.8.0_232]
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ~[?:1.8.0_232]
	at java.lang.Thread.run(Thread.java:748) [?:1.8.0_232]
Caused by: org.apache.thrift.transport.TTransportException: javax.net.ssl.SSLHandshakeException: Remote host closed connection during handshake
...
Caused by: javax.net.ssl.SSLHandshakeException: Remote host closed connection during handshake
...
Caused by: java.io.EOFException: SSL peer shut down incorrectly
...

This error message is printed when readiness and liveness probes contact HiveServer2, or when the LoadBalancer sends ping signals to HiveServer2 to check its health. Hence it does not indicate an error and can be ignored. For the user who wants to suppress such error messages, the following workaround is available.

Download TThreadPoolServer.java from the Thrift source repository (https://github.com/apache/thrift/) and copy it to a new directory ql/src/java/org/apache/thrift/server/ in the source code of Hive for MR3.

$ wget https://raw.githubusercontent.com/apache/thrift/0.9.3.1/lib/java/src/org/apache/thrift/server/TThreadPoolServer.java
$ mkdir -p ql/src/java/org/apache/thrift/server/
$ cp TThreadPoolServer.java ql/src/java/org/apache/thrift/server/

Locate the line that prints the error message.

  } catch (Exception x) {
    LOGGER.error("Error occurred during processing of message.", x);
  } finally {

Then modify the line to suppress the error message or the stack trace. For example, the user can suppress the stack trace as follows:

  } catch (Exception x) {
    LOGGER.error("Error occurred during processing of message: " + x.getClass().getName());
  } finally {

Rebuild Hive for MR3 and create a new Docker image.

9. A query accessing HDFS fails with `org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block`.

A query accessing HDFS may fail with an error like:

java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException: java.io.IOException: org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block: BP-1848301428-10.1.90.9-1589952347981:blk_1078550925_4810302 file=/tmp/tpcds-generate/9999/catalog_returns/data-m-08342
...
Caused by: org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block: BP-1848301428-10.1.90.9-1589952347981:blk_1078550925_4810302 file=/tmp/tpcds-generate/9999/catalog_returns/data-m-08342
	at org.apache.hadoop.hdfs.DFSInputStream.refetchLocations(DFSInputStream.java:875)
	at org.apache.hadoop.hdfs.DFSInputStream.chooseDataNode(DFSInputStream.java:858)
	at org.apache.hadoop.hdfs.DFSInputStream.chooseDataNode(DFSInputStream.java:837)
	at org.apache.hadoop.hdfs.DFSInputStream.blockSeekTo(DFSInputStream.java:566)
	at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:756)
	at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:825)
	at java.io.DataInputStream.read(DataInputStream.java:149)
...

This error can occur even when the HDFS block is actually available. It is usually the result of using too small values for a few configuration keys. For example, the user can try adjusting the following configuration keys.

hive.exec.max.dynamic.partitions.pernode (e.g., from the default value of 1000 to 100000)
hive.exec.max.dynamic.partitions (e.g., from the default value of 100 to 100000)
hive.exec.max.created.files (e.g., from the default value of 100000 to 1000000)

10. A query fails with too many fetch failures.

A query may fail with an error like after fetch failures:

Caused by: java.io.IOException: Map_1: Shuffle failed with too many fetch failures and insufficient progress! failureCounts=1, pendingInputs=1, fetcherHealthy=false, reducerProgressedEnough=true, reducerStalled=true

In the following example of loading 10TB TPC-DS datasets, Map 1 initially succeeds, but later reruns its Tasks because Reducer 2 experiences many fetch failures.

hive.k8s.memory.page.cache

In such a case, the user can try to reduce the chance of fetch failures or recover from fetch failures as follows:

Decrease the value for the configuration key tez.runtime.shuffle.total.parallel.copies in tez-site.xml (e.g., from 360 to 180) to reduce the total number of concurrent fetchers in each ContainerWorker.
Decrease the value for the configuration key tez.runtime.shuffle.parallel.copies in tez-site.xml (e.g., from 20 to 10) to reduce the number of fetchers per LogicalInput (all of which run in parallel). This has the effect of reducing the load on the side of shuffle handlers because fewer requests are simultaneously made from reducers.
Increase the value for the configuration key hive.mr3.am.task.max.failed.attempts (e.g., to 5). This has the effect of allowing each reducer to make more attempts to fetch input data. See Fault Tolerance for more details.
Increase the value for the configuration key tez.runtime.shuffle.connect.timeout in tez-site.xml (e.g., to 17500). See Basic Performance Tuning for more details.

11. Metastore and Ranger do not start normally when using MySQL databases (on Kubernetes).

From MR3 release 1.4, the Docker images for Metastore and Ranger from DockerHub download a MySQL Connector from https://cdn.mysql.com/Downloads/Connector-J/mysql-connector-java-8.0.28.tar.gz. To use MySQL databases, the user should check the compatibility with MySQL Connector 8.0.28.

For example, Ranger may generate an error if it uses an incompatible MySQL database.

2022-05-10 10:38:12,937  [E] Ranger all admins default password change request failed
Starting Apache Ranger Admin Service
Apache Ranger Admin Service with pid 2061 has started.

12. When executing a query calling UDFs or using JdbcStorageHandler, it fails with `ClassNotFoundException`.

By default, the configuration key mr3.am.permit.custom.user.class is set to false for security reasons, which means that InputInitializer, VertexManager, or OutputCommiter running in DAGAppMaster may not use custom Java classes. Hence executing a query calling UDFs or using JdbcStorageHandler may try to load custom Java classes and generate ClassNotFoundException, as in:

# add jar hdfs:///user/hive/custom-udf.jar;
# create temporary function json_array_explode as 'com.hive.udf.JsonArrayExplode';

# --- while executing a query calling json_array_explode 
Caused by: java.lang.ClassNotFoundException: come.hive.udf.JsonArrayExplode

# --- while executing a query using JdbcStorageHandler
Caused by: java.lang.ClassNotFoundException: org.apache.hive.storage.jdbc.JdbcInputFormat

To prevent ClassNotFoundException in such a case, set mr3.am.permit.custom.user.class to true in mr3-site.xml.

13. When using Kerberized HDFS, executing a query with no input files fails with `AccessControlException`.

If Kerberized HDFS is used, creating a fresh table or inserting values to an existing table may fail, while executing queries only reading data works okay.

... org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
...

This error occurs if the configuration key hive.mr3.dag.additional.credentials.source is not set in hive-site.xml. See Accessing Secure HDFS for details.

A similar error can occur inside DAGAppMaster while generating splits. (The log of DAGAppMaster reports credentials associated with each DAG.)

2023-08-31 15:24:19,402 [main] INFO  ContainerWorker [] - Credentials for Y@container_1694103365516_0016_01_000004: SecretKeys = 0, Tokens = 2: List(HDFS_DELEGATION_TOKEN, mr3.job)

2023-08-31 16:19:08,183 [DAG1-Input-4-3] WARN  org.apache.hadoop.ipc.Client [] - Exception encountered while connecting to the server : org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
2023-08-31 16:19:08,195 [DAG1-Map 1] ERROR Vertex [] - RootInput order_detail failed on Vertex Map 1
com.datamonad.mr3.api.common.AMInputInitializerException: order_detail
  at
  ...
Caused by: java.io.IOException: org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
  ...

In such a case, check if the configuration key dfs.encryption.key.provider.uri or hadoop.security.key.provider.path is set in core-site.xml. See Accessing Secure HDFS for details.

14. The execution fails with `OutOfMemoryError` from `PipelinedSorter.allocateSpace()`.

This usually happens when the value for the configuration key tez.runtime.io.sort.mb is too large for the amount of available memory and the type of the garbage collector in use. The user can try a smaller value for tez.runtime.io.sort.mb or set tez.runtime.pipelined.sorter.lazy-allocate.memory to false. See Performance Tuning for more details.

15. Loading a table fails with `FileAlreadyExistsException`.

Loading a table may fail with FileAlreadyExistsException, e.g.:

Caused by: org.apache.hadoop.fs.FileAlreadyExistsException: Failed to rename s3a://hivemr3/warehouse/tpcds_bin_partitioned_orc_1004.db/.hive-staging_hive_2023-05-17_07-37-59_392_7290354321306036074-2/-ext-10002/000000_0/delta_0000001_0000001_0000/bucket_00000 to s3a://hivemr3/warehouse/tpcds_bin_partitioned_orc_1004.db/web_site/delta_0000001_0000001_0000/bucket_00000; destination file exists

This usually happens when speculative executing is enabled. The user can disable speculative execution by setting the configuration key hive.mr3.am.task.concurrent.run.threshold.percent to 100 in hive-site.xml.

16. The first query executed after starting Hive on MR3 runs very slow.

This usually occurs when mr3.am.min.cluster.resource.memory.mb and mr3.am.min.cluster.resource.cpu.cores are set to too small values. Before creating ContainerWorkers, MR3 estimates the amount of cluster resources available with these two configuration parameters. If their values are too small, MR3 creates only a small number of mappers for reading input data, thus considerably delaying their completion.

17. Hive on MR3 runs slow when using Parquet.

Hive on MR3 provides better support for ORC than Parquet, so the user should prefer ORC to Parquet for performance. Parquet may result in slower performance especially if it uses DATE, DECIMAL, TIMESTAMP.

18. Metastore does not collect all statistics even with both `hive.stats.autogather` and `hive.stats.column.autogather` set to true

The user should manually execute the analyze table command.

18. `java.lang.OutOfMemoryError`

There is no universal solution to the problem of OutOfMemoryError. Here is a list of suggestions for reducing memory pressure in MR3.

Set runtime.io.sort to a smaller value in tez-site.xml. See Basic Performance Tuning.
Set tez.runtime.use.free.memory.fetched.input to false in tez-site.xml. See Basic Performance Tuning.
If OutOfMemoryError occurs during ordered shuffle, try a smaller value for tez.runtime.shuffle.merge.percent in tez-site.xml.
For executing batch queries, set mr3.container.task.failure.num.sleeps to a non-zero value in mr3-site.xml. See Basic Performance Tuning.

19. Compaction jobs get stuck in the state of `ready for cleaning`.

See Configuring Compaction.

20. Creating Iceberg tables fails.

This can happen when speculative executing is enabled. The user can disable speculative execution by setting the configuration key hive.mr3.am.task.concurrent.run.threshold.percent to 100 in hive-site.xml.

1. Metastore fails to find a MySQL connector jar file in the classpath with ClassNotFoundException (on Kubernetes).

2. When running a query, ContainerWorker Pods never get launched and Beeline gets stuck.

3. A query fails with a message No space available in any of the local directories (on Kubernetes).

4. A query accessing S3 fails with SdkClientException: Unable to execute HTTP request: Timeout waiting for connection from pool

5. A query accessing S3 makes no progress because Map vertexes get stuck in the state of Initializing.

6. DAGAppMaster Pod does not start because mr3-conf.properties does not exist.

7. Metastore fails with Version information not found in metastore

8. HiveServer2 repeatedly prints an error message server.TThreadPoolServer: Error occurred during processing of message.

9. A query accessing HDFS fails with org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block.