Apache Hadoop Known Issues

This page includes known issues and related topics, including:

Deprecated Properties

Several Hadoop and HDFS properties have been deprecated as of Hadoop 2.0.0 (Hadoop 0.23.1, CDH 4 Beta) and later. For details, see Deprecated Properties.

Hadoop Common

Zip Slip Vulnerability

“Zip Slip” is a widespread arbitrary file overwrite critical vulnerability, which typically results in remote command execution. It was discovered and responsibly disclosed by the Snyk Security team ahead of a public disclosure on June 5, 2018, and affects thousands of projects.

Cloudera has analyzed our use of zip-related software, and has determined that only Apache Hadoop is vulnerable to this class of vulnerability in CDH 5. This has been fixed in upstream Hadoop as CVE-2018-8009.

Products affected: Hadoop

Releases affected:

  • CDH 5.12.x and all prior releases
  • CDH 5.13.0, 5.13.1, 5.13.2, 5.13.3
  • CDH 5.14.0, 5.14.2, 5.14.3
  • CDH 5.15.0

Users affected: All

Date of detection: April 19, 2018

Detected by: Snyk

Severity: High

Impact: Zip Slip is a form of directory traversal that can be exploited by extracting files from an archive. The premise of the directory traversal vulnerability is that an attacker can gain access to parts of the file system outside of the target folder in which they should reside. The attacker can then overwrite executable files and either invoke them remotely or wait for the system or user to call them, thus achieving remote command execution on the victim’s machine. The vulnerability can also cause damage by overwriting configuration files or other sensitive resources, and can be exploited on both client (user) machines and servers.

CVE: CVE-2018-8009

Immediate action required: Upgrade to a version that contains the fix.

Addressed in release/refresh/patch: CDH 5.14.4, CDH 5.15.1

For the latest update on this issue, see the corresponding Knowledge article:

TSB: 2018-307: Zip Slip Vulnerability

Apache Hadoop MapReduce Job History Server (JHS) vulnerability CVE-2017-15713

A vulnerability in Hadoop’s Job History Server allows a cluster user to expose private files owned by the user running the MapReduce Job History Server (JHS) process. See http://seclists.org/oss-sec/2018/q1/79 for reference.

Products affected: Apache Hadoop MapReduce

Releases affected: All releases prior to CDH 5.12.0. CDH 5.12.0, CDH 5.12.1, CDH 5.12.2, CDH 5.13.0, CDH 5.13.1, CDH 5.14.0

Users affected: Users running the MapReduce Job History Server (JHS) daemon

Date/time of detection: November 8, 2017

Detected by: Man Yue Mo of lgtm.com

Severity (Low/Medium/High): High

Impact: The vulnerability allows a cluster user to expose private files owned by the user running the MapReduce Job History Server (JHS) process. The malicious user can construct a configuration file containing XML directives that reference sensitive files on the MapReduce Job History Server (JHS) host.

CVE: CVE-2017-15713

Immediate action required: Upgrade to a release where the issue is fixed.

Addressed in release/refresh/patch: CDH 5.13.2, 5.14.2

Hadoop LdapGroupsMapping does not support LDAPS for self-signed LDAP server

Hadoop LdapGroupsMapping does not work with LDAP over SSL (LDAPS) if the LDAP server certificate is self-signed. This use case is currently not supported even if Hadoop User Group Mapping LDAP TLS/SSL Enabled, Hadoop User Group Mapping LDAP TLS/SSL Truststore, and Hadoop User Group Mapping LDAP TLS/SSL Truststore Password are filled properly.

Bug: HADOOP-12862

Affected Versions: All CDH 5 versions.

Workaround: None.


Potential data corruption due to race conditions between concurrent block read and write

Under rare conditions when an HDFS file is open for write, an application reading the same HDFS blocks might read up-to-date block data of the partially written file, while reading a stale checksum that corresponds to the block data before the latest write. The block is incorrectly declared corrupt as a result. Normally the HDFS NameNode schedules additional replica for the same block from other replicas if a replica is corrupted, but if the frequency of concurrent write and read is high enough, there is a small probability that all replicas of a block can be declared corrupt, and the file becomes corrupt and unrecoverable as well.

DataNode might print error log such as the following:
2017-10-18 11:23:46,627 ERROR org.apache.hadoop.hdfs.server.datanode.DataNode: ip-168-61-2-30:50010:DataXceiver error processing WRITE_BLOCK operation src: / dst: /
java.io.IOException: Terminating due to a checksum error.java.io.IOException: Unexpected checksum mismatch while writing BP-1666924250- from /
at org.apache.hadoop.hdfs.server.datanode.BlockReceiver.receivePacket(BlockReceiver.java:604)
at org.apache.hadoop.hdfs.server.datanode.BlockReceiver.receiveBlock(BlockReceiver.java:894)
at org.apache.hadoop.hdfs.server.datanode.DataXceiver.writeBlock(DataXceiver.java:794)
at org.apache.hadoop.hdfs.protocol.datatransfer.Receiver.opWriteBlock(Receiver.java:169)
at org.apache.hadoop.hdfs.protocol.datatransfer.Receiver.processOp(Receiver.java:106)
at org.apache.hadoop.hdfs.server.datanode.DataXceiver.run(DataXceiver.java:246)
at java.lang.Thread.run(Thread.java:745)

The bug is fixed by HDFS-11056, HDFS-11160 and HDFS-11229.

Products Affected: HDFS

Affected Versions:
  • All CDH 5.4 releases and lower
  • CDH 5.5.0, 5.5.1, 5.5.2, 5.5.4, 5.5.5
  • CDH 5.6.0, 5.6.1
  • CDH 5.7.0, 5.7.1, 5.7.2, 5.7.3, 5.7.4, 5.7.5
  • CDH 5.8.0, 5.8.2, 5.8.3
  • CDH 5.9.0, 5.9.1

Users Affected: Workloads that require reading a file while it’s being concurrently written to HDFS.

Severity (Low/Medium/High): Low

Impact: If the workload requires reading and writing the same file concurrently, there is a small probability that all replicas of a block can be declared corrupt, and the file becomes corrupt as well.

Immediate action required: Customers are advised to upgrade to a CDH version containing the fix if the workloads are susceptible to this bug.

Fixed in Versions:
  • CDH 5.5.6 and higher
  • CDH 5.7.6 and higher
  • CDH 5.8.4 and higher
  • CDH 5.9.2 and higher
  • CDH 5.10.0 and higher

Cannot re-encrypt an encryption zone if a previous re-encryption on it was canceled

When canceling a re-encryption on an encryption zone, the status of the re-encryption may continue to show "Processing". When this occurs, future re-encrypt commands for this encryption zone will fail inside the NameNode, and the re-encryption will never complete.

Cloudera Bug: CDH-59073

Affected Versions: CDH 5.13.0

Fixed in Versions: CDH 5.13.1 and higher

Workaround: To halt, or remove the "Processing" status for the encryption zone, re-issue the cancel re-encryption command on the encryption zone. If a new re-encryption command is required for this encryption zone, restart the NameNode before issuing the command.

Potential Block Corruption and Data Loss During Pipeline Recovery

A bug in the HDFS block pipeline recovery code can cause blocks to be unrecoverable due to miscalculation of the block checksum. On a busy cluster where data is written and flushed frequently, when a write pipeline recovery occurs, a node newly added to the write pipeline may calculate the checksum incorrectly. This miscalculation is very rare, but when it does occur, the replica becomes corrupted and data can be lost if all replicas are simultaneously affected.

Bug: HDFS-4660 , HDFS-9220

Detecting this known issue requires correlating multiple log messages. Below is an example DataNode log error message captured at the time of block creation:
java.io.IOException: Terminating due to a checksum error.java.io.IOException:
Unexpected checksum mismatch while writing
BP-1800173197-10.x.y.z-1444425156296:blk_1170125248_96458336 from /10.x.y.z
This issue affects these versions of CDH:
  • CDH 5.0.0, 5.0.1, 5.0.2, 5.0.3, 5.0.4, 5.0.5, 5.0.6
  • CDH 5.1.0, 5.1.2, 5.1.3, 5.1.4, 5.1.5
  • CDH 5.2.0, 5.2.1, 5.2.3, 5.2.4, 5.2.5, 5.2.6
  • CDH 5.3.0, 5.3.1, 5.3.2, 5.3.3, 5.3.4, 5.3.5, 5.3.7, 5.3.8, 5.3.9, 5.3.10
  • CDH 5.4.0, 5.4.1, 5.4.2, 5.4.3, 5.4.4, 5.4.5, 5.4.7, 5.4.8, 5.4.9, 5.4.10
  • CDH 5.5.0, 5.5.1
Workaround: None. Upgrade to a CDH version that includes the fix: CDH 5.4.11, CDH 5.5.2, CDH 5.6.0 and higher.

Users affected: All users running the affected CDH versions and using the HDFS file system.

Severity (Low/Medium/High): High

Impact: Potential loss of block data.

Immediate action required: Upgrade to a CDH version that includes the fix, specifically:
  • CDH 5.4.11, CDH 5.5.2, CDH 5.6.0 and higher

DiskBalancer Occasionally Emits False Error Messages

Diskbalancer occasionally emits false error messages. For example:

2016-08-03 11:01:41,788 ERROR org.apache.hadoop.hdfs.server.datanode.DiskBalancer:
Disk Balancer is not enabled.

You can safely ignore this error message if you are not using DiskBalancer.

Affected Versions: CDH 5.8.1 and below.

Fixed in Versions: CDH 5.8.2 and higher.

Bug: HDFS-10588

Workaround: Use the following command against all DataNodes to suppress DiskBalancer logs:

hadoop daemonlog -setlevel <host:port> org.apache.hadoop.hdfs.server.datanode.DiskBalancer FATAL 

Another workaround is to suppress the warning by setting the log level of DiskBalancer to FATAL. Add the following to log4j.properties (DataNode Logging Advanced Configuration Snippet (Safety Valve)) and restart your DataNodes:

log4j.logger.org.apache.hadoop.hdfs.server.datanode.DiskBalancer = FATAL      

Upgrade Requires an HDFS Upgrade

Upgrading from any release earlier than CDH 5.2.0 to CDH 5.2.0 or later requires an HDFS Upgrade.

See Upgrading Unmanaged CDH Using the Command Line for further information.

Optimizing HDFS Encryption at Rest Requires Newer openssl Library on Some Systems

CDH 5.3 implements the Advanced Encryption Standard New Instructions (AES-NI), which provide substantial performance improvements. To get these improvements, you need a recent version of libcrypto.so on HDFS and MapReduce client hosts that is, any host from which you originate HDFS or MapReduce requests. Many OS versions have an older version of the library that does not support AES-NI.

See HDFS Transparent Encryption in the Encryption section of the Cloudera Security guide for instructions for obtaining the right version.

Other HDFS Encryption Known Issues

Potentially Incorrect Initialization Vector Calculation in HDFS Encryption

A mathematical error in the calculation of the Initialization Vector (IV) for encryption and decryption in HDFS could cause data to appear corrupted when read. The IV is a 16-byte value input to encryption and decryption ciphers. The calculation of the IV implemented in HDFS was found to be subtly different from that used by Java and OpenSSL cryptographic routines. The result is that data could possibly appear to be corrupted when it is read from a file inside an Encryption Zone.

Fortunately, the probability of this occurring is extremely small. For example, the maximum size of a file in HDFS is 64 TB. This enormous file would have a 1-in-4- million chance of hitting this condition. A more typically sized file of 1 GB would have a roughly 1-in-274-billion chance of hitting the condition.

Affected Versions: CDH 5.2.1 and below

Fixed in Versions: CDH 5.3.0 and higher

Cloudera Bug: CDH-23618

Workaround: If you are using the experimental HDFS encryption feature in CDH 5.2, upgrade to CDH 5.3 and verify the integrity of all files inside an Encryption Zone.

DistCp between unencrypted and encrypted locations fails

By default, DistCp compares checksums provided by the filesystem to verify that data was successfully copied to the destination. However, when copying between unencrypted and encrypted locations, the filesystem checksums will not match since the underlying block data is different.

Affected Versions: CDH 5.2.1 and below.

Fixed in Versions: CDH 5.2.2 and higher.

Bug: HADOOP-11343

Workaround: Specify the -skipcrccheck and -update distcp flags to avoid verifying checksums.

Cannot move encrypted files to trash

With HDFS encryption enabled, you cannot move encrypted files or directories to the trash directory.

Affected Versions: All CDH 5 versions

Bug: HDFS-6767

Workaround: To remove encrypted files/directories, use the following command with the -skipTrash flag specified to bypass trash.
rm -r -skipTrash /testdir

HDFS NFS gateway and CDH installation (using packages) limitation

HDFS NFS gateway works as shipped ("out of the box") only on RHEL-compatible systems, but not on SLES, Ubuntu, or Debian. Because of a bug in native versions of portmap/rpcbind, the HDFS NFS gateway does not work out of the box on SLES, Ubuntu, or Debian systems when CDH has been installed from the command-line, using packages. It does work on supported versions of RHEL-compatible systems on which rpcbind-0.2.0-10.el6 or later is installed, and it does work if you use Cloudera Manager to install CDH, or if you start the gateway as root. For more information, see supported versions.

Bug: 731542 (Red Hat), 823364 (SLES), 594880 (Debian)

Workarounds and caveats:
  • On Red Hat and similar systems, make sure rpcbind-0.2.0-10.el6 or later is installed.
  • On SLES, Debian, and Ubuntu systems, do one of the following:
    • Install CDH using Cloudera Manager; or
    • As of CDH 5.1, start the NFS gateway as root; or
    • Start the NFS gateway without using packages; or
    • You can use the gateway by running rpcbind in insecure mode, using the -i option, but keep in mind that this allows anyone from a remote host to bind to the portmap.

HDFS does not currently provide ACL support for the NFS gateway

Affected Versions: All CDH 5 versions

Bug: HDFS-6949

Cloudera Bug: CDH-26921

No error when changing permission to 777 on .snapshot directory

Snapshots are read-only; running chmod 777 on the .snapshots directory does not change this, but does not produce an error (though other illegal operations do).

Affected Versions: All CDH 5 versions

Bug: HDFS-4981

Cloudera Bug: CDH-13062

Workaround: None

Snapshot operations are not supported by ViewFileSystem

Affected Versions: All CDH 5 versions

Cloudera Bug: CDH-12600

Workaround: None

Snapshots do not retain directories' quotas settings

Affected Versions: All CDH 5 versions

Bug: HDFS-4897

Workaround: None

Permissions for dfs.namenode.name.dir incorrectly set.

Hadoop daemons should set permissions for the dfs.namenode.name.dir (or dfs.name.dir) directories to drwx------ (700), but in fact these permissions are set to the file-system default, usually drwxr-xr-x (755).

Affected Versions: All CDH 5 versions

Bug: HDFS-2470

Workaround: Use chmod to set permissions to 700. See Configuring Local Storage Directories for Use by HDFS for more information and instructions.

hadoop fsck -move does not work in a cluster with host-based Kerberos

Affected Versions: All CDH 5 versions

Cloudera Bug: CDH-7017

Workaround: Use hadoop fsck -delete

HttpFS cannot get delegation token without prior authenticated request

A request to obtain a delegation token cannot initiate an SPNEGO authentication sequence; it must be accompanied by an authentication cookie from a prior SPNEGO authentication sequence.

Affected Versions: CDH 5.1 and below

Fixed in Versions: CDH 5.2 and higher

Bug: HDFS-3988

Cloudera Bug: CDH-8144

Workaround: Make another WebHDFS request (such as GETHOMEDIR) to initiate an SPNEGO authentication sequence and then make the delegation token request.

DistCp does not work between a secure cluster and an insecure cluster in some cases

See the upstream bug reports for details.

Affected Versions: All CDH 5 versions

Bug: HDFS-7037, HADOOP-10016, HADOOP-8828

Cloudera Bug: CDH-14945, CDH-18779

Workaround: None

Port configuration required for DistCp to Hftp from secure cluster (SPNEGO)

To copy files using DistCp to Hftp from a secure cluster using SPNEGO, you must configure the dfs.https.port property on the client to use the HTTP port (50070 by default).

Affected Versions: All CDH 5 versions

Bug: HDFS-3983

Cloudera Bug: CDH-8118

Workaround: Configure dfs.https.port to use the HTTP port on the client

Non-HA DFS Clients do not attempt reconnects

This problem means that streams cannot survive a NameNode restart or network interruption that lasts longer than the time it takes to write a block.

Affected Versions: All CDH 5 versions

Bug: HDFS-4389

Cloudera Bug: CDH-10415

DataNodes may become unresponsive to block creation requests

DataNodes may become unresponsive to block creation requests from clients when the directory scanner is running.

Affected Versions: CDH 5.2.1 and below

Fixed in Versions: CDH 5.2.2 and higher

Bug: HDFS-7489

Workaround: Disable the directory scanner by setting dfs.datanode.directoryscan.interval to -1.

The active NameNode will not accept an fsimage sent from the standby during rolling upgrade

The result is that the NameNodes fail to checkpoint until the upgrade is finalized.

Affected Versions: CDH 5.3.7 and below

Fixed in Versions: CDH 5.3.8 and higher

Bug: HDFS-7185

Workaround: None.

Block report can exceed maximum RPC buffer size on some DataNodes

On a DataNode with a large number of blocks, the block report may exceed the maximum RPC buffer size.

Affected Versions: All CDH 5 versions

Bug: None

Workaround: Increase the value ipc.maximum.data.length in hdfs-site.xml:

DistCp to S3a fails due to integer overflow in retry timer

Writing to Amazon S3 under high load can cause com.amazonaws.AmazonClientException: Unable to complete transfer: timeout value is negative.

Affected Versions: All CDH 5 versions

Bug: HADOOP-12267

Cloudera Bug: CDH-29525

Workaround: Reduce the load to S3 by reducing the number of reducers or mappers.

Misapplied user-limits setting possible

The ulimits setting in /etc/security/limits.conf is applied to the wrong user when security is enabled.

Affected Versions: CDH 5.2.0 and below

Bug: DAEMON-192

Anticipated Resolution: None

Workaround: To increase the ulimits applied to DataNodes, you must change the ulimit settings for the root user, not the hdfs user.

LAZY_PERSIST storage policy is experimental and not supported

Using this storage policy could potentially lead to data loss.

Affected versions: All CDH 5 versions

Bug: HDFS-8229

Workaround: None

MapReduce2, YARN

YARN scheduler queue ACLs are not checked when performing MoveApplicationAcrossQueues operations

The YARN moveApplicationAcrossQueues operation does not check ACLs on the target queue. This allows a user to move an application to a queue that the user has no access to.

Affected Versions: All CDH 5 versions

Fixed Versions: CDH 6.0.0

Bug: YARN-5554

Cloudera Bug: CDH-43327

Workaround: N/A

Hadoop YARN Privilege Escalation CVE-2016-6811

A vulnerability in Hadoop YARN allows a user who can escalate to the yarn user the ability to possibly run arbitrary commands as the root user.

Products affected: Hadoop YARN

Releases affected:

  • CDH 5.12.x and all prior releases
  • CDH 5.13.0, 5.13.1, 5.13.2, 5.13.3
  • CDH 5.14.0, 5.14.2, 5.14.3
  • CDH 5.15.0

Users affected: Users running the Hadoop YARN service.

Detected by: Freddie Rice

Severity: High

Impact: The vulnerability allows a user who has access to a node in the cluster running a YARN NodeManager and who can escalate to the yarn user, the ability to run arbitrary commands as the root user even if the user is not allowed to escalate directly to the root user.

CVE: CVE-2016-6811

Upgrade: Upgrade to a release where the issue is fixed.

Workaround: The vulnerability can be mitigated by restricting access to the nodes where the YARN NodeManagers are deployed, and by removing su access to the yarn user and by making sure no one other than the yarn user is a member of the yarn group. Please consult with your internal system administration team and adhere to your internal security policy when evaluating the feasibility of the above mitigation steps.

Addressed in release/refresh/patch: CDH 5.14.4, 5.15.1

For the latest update on this issue, see the corresponding Knowledge article:

TSB: 2018-309: Hadoop YARN privilege escalation

Missing results in Hive, Spark, Pig, Custom MapReduce jobs, and other Java applications when filtering Parquet data written by Impala

Apache Hive and Apache Spark rely on Apache Parquet's parquet-mr Java library to perform filtering of Parquet data stored in row groups. Those row groups contain statistics that make the filtering efficient without having to examine every value within the row group.

Recent versions of the parquet-mr library contain a bug described in PARQUET-1217. This bug causes filtering to behave incorrectly if only some of the statistics for a row group are written. Starting in CDH 5.13, Apache Impala populates statistics in this way for Parquet files. As a result, Hive and Spark may incorrectly filter Parquet data that is written by Impala.

In CDH 5.13, Impala started writing Parquet's null_count metadata field without writing the min and max fields. This is valid, but it triggers the PARQUET-1217 bug in the predicate push-down code of the Parquet Java library (parquet-mr). If the null_count field is set to a non-zero value, parquet-mr assumes that min and max are also set and reads them without checking whether they are actually there. If those fields are not set, parquet-mr reads their default value instead.

For integer SQL types, the default value is 0, so parquet-mr incorrectly assumes that the min and max values are both 0. This causes the problem when filtering data. Unless the value 0 itself matches the search condition, all row groups are discarded due to the incorrect min/max values, which leads to missing results.

Affected Products: The Parquet Java library (parquet-mr) and by extension, all Java applications reading Parquet files, including, but not limited to:
  • Hive
  • Spark
  • Pig
  • Custom MapReduce jobs
Affected Versions:
  • CDH 5.13.0, 5.13.1, 5.13.2, and 5.14.0
  • CDS 2.2 Release 2 Powered by Apache Spark and earlier releases on CDH 5.13.0 and later

Who Is Affected: Anyone writing Parquet files with Impala and reading them back with Hive, Spark, or other Java-based components that use the parquet-mr libraries for reading Parquet files.

Severity (Low/Medium/High): High

Impact: Parquet files containing null values for integer fields written by Impala produce missing results in Hive, Spark, and other Java applications when filtering by the integer field.

Immediate Action Required:
  • Upgrade

    You should upgrade to one of the fixed maintenance releases mentioned below.

  • Workaround

    This issue can be avoided at the price of performance by disabling predicate push-down optimizations:
    • In Hive, use the following SET command:

      SET hive.optimize.ppd = false;

    • In Spark, disable the following configuration setting:

      --conf spark.sql.parquet.filterPushdown=false

Addressed in the Following Releases:
  • CDH 5.13.3 and higher
  • CDH 5.14.2 and higher
  • CDH 5.15.0 and higher
  • CDS 2.3 Release 2 and higher

For the latest update on this issue, see the corresponding Knowledge Base article:

TSB:2018-300: Missing results in Hive, Spark, Pig, and other Java applications when filtering Parquet data written by Impala

Apache Hadoop Yarn Fair Scheduler might stop assigning containers when preemption is on

In CDH 5.11.0 the preemption code was updated to improve preemption behavior. Further changes were implemented in CDH 5.11.1 and CDH 5.12.0 to fix a remaining issue as described in YARN-6432 (FairScheduler: Reserve preempted resources for corresponding applications). This fix resulted in two possible side effects:
  • A race condition that results in the Fair Scheduler making duplicate reservations. The duplicate reservations are never released and can result in an integer overflow stopping container assignments.
  • A possible deadlock in the event processing of the Fair Scheduler. This will stop all updates in the Resource Manager.

Both side effects will ultimately cause the Fair Scheduler to stop processing resource requests.

Without the change from YARN-6432 the resources that are released after being preempted are not reserved for the starved application. This could result in scheduler assigning the preempted container to any application, not just the starved application. If no reservations are made on the node for the starved application preemption will be less effective in solving the resource starvation.

Products affected: YARN

Releases affected: CDH 5.11.1, 5.12.0

Users affected: Users who have YARN configured with the FairScheduler and have turned preemption on.

Severity (Low/Medium/High): Low

Impact: The Resource Manager will accept application but no application will change state or get container assigned and thus progress.

Immediate action required:
  • If you have not upgraded to the affected release and preemption in the FairScheduler is in use, avoid upgrading to the affected releases.
  • If you have already upgraded to the affected releases, choose from the following options:
    • Upgrade to CDH 5.11.2 or 5.12.1
    • Turn off preemption

Fixed in CDH versions 5.11.2, 5.12.1.

Yarn's Continuous Scheduling can cause slowness in Oozie

When Continuous Scheduling is enabled in Yarn, this can cause slowness in Oozie due to long delays in communicating with Yarn. In Cloudera Manager 5.9.0 and higher, Enable Fair Scheduler Continuous Scheduler is turned off by default.

Affected Versions: All CDH 5 versions

Bug: None

Cloudera Bug: CDH-60788

Workaround: Turn off Enable Fair Scheduler Continuous Scheduling in Cloudera Manager's Yarn Configuration. To keep equivalent benefits of this feature, turn on Fair Scheduler Assign Multiple Tasks.

Rolling upgrades to 5.11.0 and 5.11.1 may cause application failures

Affected Versions: CDH versions that can be upgraded to 5.11.0 or 5.11.1

Fixed in Versions: CDH 5.11.2 and higher

Bug: None

Cloudera Bug: CDH-55284, TSB-241

Workaround: Upgrade to 5.11.2 or higher.

Name resolution issues can result in unresponsive Web UI and REST endpoints

Name resolution issues can cause the Web UI or the RM REST endpoints to consume all ResourceManager request handling threads, leaving the Web UI and REST endpoints unresponsive.

Fixed in Versions: CDH 5.10.0 and higher

Bug: YARN-4767

Cloudera Bug: CDH-45597

Workaround: Restart the ResourceManager or kill the application that is being accessed or waiting for the ResourceManager to complete the job.

Loss of connection to the Zookeeper cluster can cause problems with the ResourceManagers

Loss of connection to the Zookeeper cluster can cause the ResourceManagers to be in active-active state for an extended period of time.

Fixed in Versions: CDH 5.10.0 and higher

Bug: YARN-5677, YARN-5694

Cloudera Bug: CDH-45210

Workaround: None.

If the YARN user is granted access to all keys in KMS, then files localized from an encryption zone can be world readable

If the YARN user is granted access to all keys in KMS, then files localized from an encryption zone can be world readable.

Fixed in Versions: CDH 5.7.7, 5.8.5, 5.9.2, 5.10.1, 5.11.0 and higher.

Bug: None

Cloudera Bug: CDH-47377

Workaround: Make sure files in an encryption zone do not have world-readable files modes if they are going to be localized.

Zookeeper outage can cause the ResourceManagers to exit

Fixed in Versions: CDH 5.12.0 and higher

Bug: YARN-3742

Cloudera Bug: CDH-47439

Workaround: None.

FairScheduler might not Assign Containers

Under certain circumstances, turning on Fair Scheduler Assign Multiple Tasks (yarn.scheduler.fair.assignmultiple) causes the scheduler to stop assigning containers to applications. Possible symptoms are that running applications show no progress, and new applications do not start, staying in an Assigned state, despite the availability of free resources on the cluster.

Affected Versions: CDH 5.5.0, CDH-5.5.1, CDH-5.5.2, CDH-5.5.3, CDH-5.5.4, CDH-5.5.5, CDH-5.5.6, CDH-5.6.0, and CDH-5.6.1

Fixed in Versions: CDH 5.7.0 and higher

Bug: YARN-4477

Cloudera Bug: CDH-36686

Workaround: Turn off Fair Scheduler Assign Multiple Tasks (yarn.scheduler.fair.assignmultiple) and restart the ResourceManager.

FairScheduler: AMs can consume all vCores leading to a livelock

When using FAIR policy with the FairScheduler, Application Masters can consume all vCores which may lead to a livelock.

Fixed in Versions: CDH 5.7.3 and higher, except for CDH 5.8.0 and CDH 5.8.1

Bug: YARN-4866

Cloudera Bug: CDH-37529

Workaround: Use Dominant Resource Fairness (DRF) instead of FAIR; or make sure that the cluster has enough vCores in proportion to the memory.

NodeManager mount point mismatch (YARN)

NodeManager may select a cgroups (Linux control groups) mount point that is not accessible to user yarn, resulting in failure to start up. The mismatch occurs because YARN uses cgroups in mount point /run/lxcfs/controllers, while Cloudera Manager typically configures cgroups at /sys/fs/cgroups. This issue has occurred on Ubuntu 16.04 systems.

Fixed in Versions: CDH 5.11.1 and higher

Bug: YARN-6433

Cloudera Bug: CDH-52263

Workaround: Look through your YARN logs to identify the failing mount point, and unmount it:
$ umount errant_mount_point
You can also:
  1. apt-get remove lxcfs
  2. Reboot the node

JobHistory URL mismatch after server relocation

After moving the JobHistory Server to a new host, the URLs listed for the JobHistory Server on the ResourceManager web UI still point to the old JobHistory Server. This affects existing jobs only. New jobs started after the move are not affected.

Affected Versions: All CDH 5 versions.

Workaround: For any existing jobs that have the incorrect JobHistory Server URL, there is no option other than to allow the jobs to roll off the history over time. For new jobs, make sure that all clients have the updated mapred-site.xml that references the correct JobHistory Server.

Starting an unmanaged ApplicationMaster may fail

Starting a custom Unmanaged ApplicationMaster may fail due to a race in getting the necessary tokens.

Affected Versions: CDH 5.1.5 and below.

Fixed in Versions: CDH 5.2 and higher.

Bug: YARN-1577

Cloudera Bug: CDH-17405

Workaround: Try to get the tokens again; the custom unmanaged ApplicationMaster should be able to fetch the necessary tokens and start successfully.

Moving jobs between queues not persistent after restart

CDH 5 adds the capability to move a submitted application to a different scheduler queue. This queue placement is not persisted across ResourceManager restart or failover, which resumes the application in the original queue.

Affected Versions: All CDH 5 versions.

Bug: YARN-1558

Cloudera Bug: CDH-17408

Workaround: After ResourceManager restart, re-issue previously issued move requests.

Encrypted shuffle may fail (MRv2, Kerberos, TLS)

In MRv2, if the LinuxContainerExecutor is used (usually as part of Kerberos security), and hadoop.ssl.enabled is set to true (see Configuring Encrypted Shuffle, Encrypted Web UIs, and Encrypted HDFS Transport), then the encrypted shuffle does not work and the submitted job fails.

Affected Versions: All CDH 5 versions.


Cloudera Bug: CDH-8036

Workaround: Use encrypted shuffle with Kerberos security without encrypted web UIs, or use encrypted shuffle with encrypted web UIs without Kerberos security.

ResourceManager-to-Application Master HTTPS link fails

In MRv2 (YARN), if hadoop.ssl.enabled is set to true (use HTTPS for web UIs), then the link from the ResourceManager to the running MapReduce Application Master fails with an HTTP Error 500 because of a PKIX exception.

A job can still be run successfully, and, when it finishes, the link to the job history does work.

Affected Versions: CDH versions before 5.1.0.

Fixed Versions: CDH 5.1.0

Bug: YARN-113

Cloudera Bug: CDH-8014

Workaround: Do not use encrypted web UIs.

History link in ResourceManager web UI broken for killed Spark applications

When a Spark application is killed, the history link in the ResourceManager web UI does not work.

Workaround: To view the history for a killed Spark application, see the Spark HistoryServer web UI instead.

Affected Versions: All CDH versions

Apache Issue: None

Cloudera Issue: CDH-49165

Routable IP address required by ResourceManager

ResourceManager requires routable host:port addresses for yarn.resourcemanager.scheduler.address, and does not support using the wildcard address.

Bug: None

Cloudera Bug: CDH-6808

Workaround: Set the address, in the form host:port, either in the client-side configuration, or on the command line when you submit the job.

Amazon S3 copy may time out

The Amazon S3 filesystem does not support renaming files, and performs a copy operation instead. If the file to be moved is very large, the operation can time out because S3 does not report progress to the TaskTracker during the operation.


Cloudera Bug: CDH-17955

Workaround: Use -Dmapred.task.timeout=15000000 to increase the MR task timeout.

Out-of-memory errors may occur with Oracle JDK 1.8

The total JVM memory footprint for JDK8 can be larger than that of JDK7 in some cases. This may result in out-of-memory errors.

Bug: None

Workaround: Increase max default heap size (-Xmx). In the case of MapReduce, for example, increase Reduce Task Maximum Heap Size in Cloudera Manager (mapred.reduce.child.java.opts, or mapreduce.reduce.java.opts for YARN) to avoid out-of-memory errors during the shuffle phase.

MapReduce JAR file renamed (CDH 5.4.0)

As of CDH 5.4.0, hadoop-test.jar has been renamed to hadoop-test-mr1.jar. This JAR file contains the mrbench, TestDFSIO, and nnbench tests.

Bug: None

Cloudera Bug: CDH-26521

Workaround: None.

Jobs in pool with DRF policy will not run if root pool is FAIR

If a child pool using DRF policy has a parent pool using Fairshare policy, jobs submitted to the child pool do not run.

Affected Versions: All CDH 5 versions.

Bug: YARN-4212

Cloudera Bug: CDH-31358

Workaround: Change parent pool to use DRF.

Jobs with encrypted spills do not recover if the AM goes down

The fix to CVE-2015-1776 leads to not having enough information to recover a job should the Application Master fail. Releases with this security fix cannot tolerate Application Master failures.

Affected Versions: All CDH 5 versions.


Cloudera Bug: CDH-37412

Workaround: None. Fix to come in a later release.

Large TeraValidate data sets can fail with MapReduce

In a cluster using MapReduce, TeraValidate fails when run over large TeraGen/TeraSort data sets (1TB and larger) with an IndexOutOfBoundsException. Smaller data sets do not show this issue.

Affected Versions: CDH 5.3.7 and lower

Fixed in Versions: CDH 5.3.8 and higher


Cloudera Bug: CDH-31871


MapReduce job failure and rolling upgrade (CDH 5.6.0)

MapReduce jobs might fail during a rolling upgrade to or from CDH 5.6.0. Cloudera recommends that you avoid doing rolling upgrades to CDH 5.6.0.

Bug: None

Cloudera Bug: CDH-38587

Workaround: Restart failed jobs.

Unsupported Features

The following features are not currently supported:
  • FileSystemRMStateStore: Cloudera recommends you use ZKRMStateStore (ZooKeeper-based implementation) to store the ResourceManager's internal state for recovery on restart or failover. Cloudera does not support the use of FileSystemRMStateStore in production.
  • ApplicationTimelineServer (also known as Application History Server): Cloudera does not support ApplicationTimelineServer v1. ApplicationTimelineServer v2 is under development and Cloudera does not currently support it.
  • Scheduler Reservations: Scheduler reservations are currently at an experimental stage, and Cloudera does not support their use in production.
  • Scheduler node-labels: Node-labels are currently experimental with CapacityScheduler. Cloudera does not support their use in production.
  • CapacityScheduler. This is deprecated and will be removed from CDH in a future version.


Oozie workflows not recovered after JobTracker failover on a secure cluster

Delegation tokens created by clients (via JobClient#getDelegationToken()) do not persist when the JobTracker fails over. This limitation means that Oozie workflows will not be recovered successfully in the event of a failover on a secure cluster.

Bug: None

Cloudera Bug: CDH-8913

Workaround: Re-submit the workflow.

Hadoop Pipes should not be used in secure clusters

Hadoop Pipes should not be used in secure clusters. A shared password used by the framework for parent-child communications in the clear. A malicious user could intercept that password and potentially use it to access private data in a running application.

Bug: None

No JobTracker becomes active if both JobTrackers are migrated to other hosts

If JobTrackers in an High Availability configuration are shut down, migrated to new hosts, then restarted, no JobTracker becomes active. The logs show a Mismatched address exception.

Bug: None

Cloudera Bug: CDH-11801

Workaround: After shutting down the JobTrackers on the original hosts, and before starting them on the new hosts, delete the ZooKeeper state using the following command:
$ zkCli.sh rmr /hadoop-ha/<logical name>

Hadoop Pipes may not be usable in an MRv1 Hadoop installation done through tarballs

Under MRv1, MapReduce's C++ interface, Hadoop Pipes, may not be usable with a Hadoop installation done through tarballs unless you build the C++ code on the operating system you are using.

Bug: None

Cloudera Bug: CDH-7304

Workaround: Build the C++ code on the operating system you are using. The C++ code is present under src/c++ in the tarball.