Known Issues and Workarounds in Impala
The following sections describe known issues and workarounds in Impala.
For issues fixed in various Impala releases, see Fixed Issues in Impala .
Known Issues in the Current Production Release (Impala 2.0.0)
These known issues affect the current release. Any workarounds are listed here. The bug links take you to the Impala issues site, where you can see the diagnosis and whether a fix is in the pipeline.
- Memory leak using zlib on CentOS6 (and possibly other platforms)
- Memory Limit Exceeded Error when running with multiple clients
- ORDER BY rand() does no work.
- Loading metadata for an extremely wide table (10k+ columns) takes too long
- Impala BE cannot parse Avro schema that contains a trailing semi-colon
- Process mem limit does not account for the JVM's memory usage
- Impala Parser issue when using fully qualified table names that start with a number.
- CatalogServer should not require HBase to be up to reload its metadata
- Kerberos tickets must be renewable
- Avro Scanner fails to parse some schemas
- Configuration needed for Flume to be compatible with Impala
- Impala does not support running on clusters with federated namespaces
- Deviation from Hive behavior: Out of range values float/double values are returned as maximum allowed value of type (Hive returns NULL)
- Deviation from Hive behavior: Impala does not do implicit casts between string and numeric and boolean types.
- If Hue and Impala are installed on the same host, and if you configure Hue Beeswax in CDH 4.1 to execute Impala queries, Beeswax cannot list Hive tables and shows an error on Beeswax startup.
- Impala should tolerate bad locale settings
- Log Level 3 Not Recommended for Impala
Memory leak using zlib on CentOS6 (and possibly other platforms)
Unreleased memory could accumulate as more and more queries are run. The cause is thought to be a bug in version 1.2.3 of the zlib library, which is used in CentOS 6.4 and possibly other Linux releases. Impala uses this library internally to compress query profiles.
Resolution: Under investigation
Memory Limit Exceeded Error when running with multiple clients
Out-of-memory errors could occur if multiple concurrent queries utilize the
Workaround: Either run such queries concurrently using a mechanism such as admission control, or reduce the memory limit for each query so that the spilling operation is triggered sooner. For example, if two queries are encountering this issue when running with MEM_LIMIT=4g, reduce the memory limit for each query by half, to 2 GB.
ORDER BY rand() does no work.
Because the value for rand() is computed early in a query, using an ORDER BY expression involving a call to rand() does not actually randomize the results.
Loading metadata for an extremely wide table (10k+ columns) takes too long
The first access to a table could take substantial time if the table has thousands of columns.
Workaround: Use tables with fewer columns, and join where necessary.
Impala BE cannot parse Avro schema that contains a trailing semi-colon
If an Avro table has a schema definition with a trailing semicolon, Impala encounters an error when the table is queried.
Process mem limit does not account for the JVM's memory usage
Some memory allocated by the JVM used internally by Impala is not counted against the memory limit for the impalad daemon.
Workaround: To monitor overall memory usage, use the top command, or add the memory figures in the Impala web UI /memz tab to JVM memory usage shown on the /metrics tab.
Impala Parser issue when using fully qualified table names that start with a number.
A fully qualified table name starting with a number could cause a parsing error. In a name such as db.571_market, the decimal point followed by digits is interpreted as a floating-point number.
Workaround: Surround each part of the fully qualified name with backticks (``).
CatalogServer should not require HBase to be up to reload its metadata
If HBase is unavailable during Impala startup or after an INVALIDATE METADATA statement, the catalogd daemon could go into an error loop, making Impala unresponsive.
Workaround: For systems not managed by Cloudera Manager, add the following settings to /etc/impala/conf/hbase-site.xml:
<property> <name>hbase.client.retries.number</name> <value>3</value> </property> <property> <name>hbase.rpc.timeout</name> <value>3000</value> </property>
Currently, Cloudera Manager does not have an Impala-only override for HBase settings, so any HBase configuration change you make through Cloudera Manager would take affect for all HBase applications. Therefore, this change is not recommended on systems managed by Cloudera Manager.
Kerberos tickets must be renewable
In a Kerberos environment, the impalad daemon might not start if Kerberos tickets are not renewable.
Workaround: Configure your KDC to allow tickets to be renewed, and configure krb5.conf to request renewable tickets.
Avro Scanner fails to parse some schemas
Querying certain Avro tables could cause a crash or return no rows, even though Impala could DESCRIBE the table.
Workaround: Swap the order of the fields in the schema specification. For example, ["null", "string"] instead of ["string", "null"].
Resolution: Not allowing this syntax agrees with the Avro specification, so it may still cause an error even when the crashing issue is resolved.
Configuration needed for Flume to be compatible with Impala
For compatibility with Impala, the value for the Flume HDFS Sink hdfs.writeFormat must be set to Text, rather than its default value of Writable. The hdfs.writeFormat setting must be changed to Text before creating data files with Flume; otherwise, those files cannot be read by either Impala or Hive.
Resolution: This information has been requested to be added to the upstream Flume documentation.
Impala does not support running on clusters with federated namespaces
Impala does not support running on clusters with federated namespaces. The impalad process will not start on a node running such a filesystem based on the org.apache.hadoop.fs.viewfs.ViewFs class.
Anticipated Resolution: Limitation
Workaround: Use standard HDFS on all Impala nodes.
Deviation from Hive behavior: Out of range values float/double values are returned as maximum allowed value of type (Hive returns NULL)
Impala behavior differs from Hive with respect to out of range float/double values. Out of range values are returned as maximum allowed value of type (Hive returns NULL).
Deviation from Hive behavior: Impala does not do implicit casts between string and numeric and boolean types.
Anticipated Resolution: None
Workaround: Use explicit casts.
If Hue and Impala are installed on the same host, and if you configure Hue Beeswax in CDH 4.1 to execute Impala queries, Beeswax cannot list Hive tables and shows an error on Beeswax startup.
Hue requires Beeswaxd to be running in order to list the Hive tables. Because of a port conflict bug in Hue in CDH4.1, when Hue and Impala are installed on the same host, an error page is displayed when you start the Beeswax application, and when you open the Tables page in Beeswax.
Anticipated Resolution: Fixed in an upcoming CDH4 release
Workarounds: Choose one of the following workarounds (but only one):
- Install Hue and Impala on different hosts. OR
Upgrade to CDH4.1.2 and add the following property in the
beeswax section of the
/etc/hue/hue.ini configuration file:
If you are using CDH4.1.1 and you want to install Hue and Impala on the same host, change the code in this
Replace line 66:
With this line:
Beeswaxd will then use port 8004.Note
If you used Cloudera Manager to install Impala, refer to the Cloudera Manager release notes for information about using an equivalent workaround by specifying the beeswax_meta_server_only=9004 configuration value in the options field for Hue. In Cloudera Manager 4, these fields are labelled Safety Valve; in Cloudera Manager 5, they are called Advanced Configuration Snippet.
Impala should tolerate bad locale settings
If the LC_* environment variables specify an unsupported locale, Impala does not start.
Workaround: Add LC_ALL="C" to the environment settings for both the Impala daemon and the Statestore daemon. See Modifying Impala Startup Options for details about modifying these environment settings.
Resolution: Fixing this issue would require an upgrade to Boost 1.47 in the Impala distribution.
Log Level 3 Not Recommended for Impala
The extensive logging produced by log level 3 can cause serious performance overhead and capacity issues.
Workaround: Reduce the log level to its default value of 1, that is, GLOG_v=1. See Setting Logging Levels for details about the effects of setting different logging levels.