Known Issues in Apache Impala

This topic describes known issues and workarounds for using Impala in this release of Cloudera Runtime.

Impala known limitation when querying compacted tables

When the compaction process deletes the files for a table from the underlying HDFS location, the Impala service does not detect the changes as the compactions does not allocate new write ids. When the same table is queried from Impala it throws a 'File does not exist' exception that looks something like this:

Query Status: Disk I/O error on <node>:22000: Failed to open HDFS file hdfs://nameservice1/warehouse/tablespace/managed/hive/<database>/<table>/xxxxx
Error(2): No such file or directory Root cause: RemoteException: File does not exist: /warehouse/tablespace/managed/hive/<database>/<table>/xxxx

Use the REFRESH/INVALIDATE statements on the affected table to overcome the 'File does not exist' exception.

Queries stuck on failed HDFS calls and not timing out

In Impala 3.2 and higher, if the following error appears multiple times in a short duration while running a query, it would mean that the connection between the impalad and the HDFS NameNode is in a bad state.

"hdfsOpenFile() for <filename> at backend <hostname:port> failed to finish before the <hdfs_operation_timeout_sec> second timeout " 

In Impala 3.1 and lower, the same issue would cause Impala to wait for a long time or not respond without showing the above error message.

Workaround: Restart the impalad.

Apache JIRA: HADOOP-15720

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.

Apache JIRA: IMPALA-532

Configuration to prevent crashes caused by thread resource limits

Impala could encounter a serious error due to resource usage under very high concurrency. The error message is similar to:

F0629 08:20:02.956413 29088 llvm-codegen.cc:111] LLVM hit fatal error: Unable to allocate section memory!
terminate called after throwing an instance of 'boost::exception_detail::clone_impl<boost::exception_detail::error_info_injector<boost::thread_resource_error> >'

          

Workaround: To prevent such errors, configure each host running an impalad daemon with the following settings:

            echo 2000000 > /proc/sys/kernel/threads-max
            echo 2000000 > /proc/sys/kernel/pid_max
            echo 8000000 > /proc/sys/vm/max_map_count
          

Add the following lines in /etc/security/limits.conf:

            impala soft nproc 262144
            impala hard nproc 262144
          

Apache JIRA: IMPALA-5605

Avro Scanner fails to parse some schemas

The default value in Avro schema must match type of first union type, e.g. if the default value is null, then the first type in the UNION must be "null".

Workaround: Swap the order of the fields in the schema specification. For example, use ["null", "string"] instead of ["string", "null"]. Note that the files written with the problematic schema must be rewritten with the new schema because Avro files have embedded schemas.

Apache JIRA: IMPALA-635

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.

Apache JIRA: IMPALA-691

Ranger audit logs for applying column masking policies missing

Impala is not producing these logs.

Workaround: None.

Apache JIRA: IMPALA-9350

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.

Workaround: Remove trailing semicolon from the Avro schema.

Apache JIRA: IMPALA-1024

Incorrect results with basic predicate on CHAR typed column

When comparing a CHAR column value to a string literal, the literal value is not blank-padded and so the comparison might fail when it should match.

Workaround: Use the RPAD() function to blank-pad literals compared with CHAR columns to the expected length.

Apache JIRA: IMPALA-1652

ImpalaODBC: Can not get the value in the SQLGetData(m-x th column) after the SQLBindCol(m th column)

If the ODBC SQLGetData is called on a series of columns, the function calls must follow the same order as the columns. For example, if data is fetched from column 2 then column 1, the SQLGetData call for column 1 returns NULL.

Workaround: Fetch columns in the same order they are defined in the table.

Apache JIRA: IMPALA-1792

Casting scenarios with invalid/inconsistent results

Using a CAST() function to convert large literal values to smaller types, or to convert special values such as NaN or Inf, produces values not consistent with other database systems. This could lead to unexpected results from queries.

Apache JIRA: IMPALA-1821

A failed CTAS does not drop the table if the insert fails

If a CREATE TABLE AS SELECT operation successfully creates the target table but an error occurs while querying the source table or copying the data, the new table is left behind rather than being dropped.

Workaround: Drop the new table manually after a failed CREATE TABLE AS SELECT

Apache JIRA: IMPALA-2005

% escaping does not work correctly when occurs at the end in a LIKE clause

If the final character in the RHS argument of a LIKE operator is an escaped \% character, it does not match a % final character of the LHS argument.

Apache JIRA: IMPALA-2422

Crash: impala::Coordinator::ValidateCollectionSlots

A query could encounter a serious error if includes multiple nested levels of INNER JOIN clauses involving subqueries.

Apache JIRA: IMPALA-2603

Incorrect result due to constant evaluation in query with outer join

Workaround: An OUTER JOIN query could omit some expected result rows due to a constant such as FALSE in another join clause. For example:

explain SELECT 1 FROM alltypestiny a1
  INNER JOIN alltypesagg a2 ON a1.smallint_col = a2.year AND false
  RIGHT JOIN alltypes a3 ON a1.year = a1.bigint_col;
+-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-+
| Explain String                                          |
+-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-+
| Estimated Per-Host Requirements: Memory=1.00KB VCores=1 |
|                                                         |
| 00:EMPTYSET                                             |
+-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-+

          

Apache JIRA: IMPALA-3094

Breakpad minidumps can be very large when the thread count is high

The size of the breakpad minidump files grows linearly with the number of threads. By default, each thread adds 8 KB to the minidump size. Minidump files could consume significant disk space when the daemons have a high number of threads.

Workaround: Add -\-minidump_size_limit_hint_kb=size to set a soft upper limit on the size of each minidump file. If the minidump file would exceed that limit, Impala reduces the amount of information for each thread from 8 KB to 2 KB. (Full thread information is captured for the first 20 threads, then 2 KB per thread after that.) The minidump file can still grow larger than the "hinted" size. For example, if you have 10,000 threads, the minidump file can be more than 20 MB.

Apache JIRA: IMPALA-3509

Impala requires FQDN from hostname command on Kerberized clusters

The method Impala uses to retrieve the host name while constructing the Kerberos principal is the gethostname() system call. This function might not always return the fully qualified domain name, depending on the network configuration. If the daemons cannot determine the FQDN, Impala does not start on a Kerberized cluster.

Workaround: Test if a host is affected by checking whether the output of the hostname command includes the FQDN. On hosts where hostname, only returns the short name, pass the command-line flag ‑‑hostname=fully_qualified_domain_name in the startup options of all Impala-related daemons.

Apache JIRA: IMPALA-4978

Metadata operations block read-only operations on unrelated tables

Metadata operations that change the state of a table, like COMPUTE STATS or ALTER RECOVER PARTITIONS, may delay metadata propagation of unrelated unloaded tables triggered by statements like DESCRIBE or SELECT queries.

Workaround:

Apache JIRA: IMPALA-6671

Impala does not support Heimdal Kerberos

Apache JIRA: IMPALA-7072

CDPD-28139: Set spark.hadoop.hive.stats.autogather to false by default

As an Impala user, if you submit a query against a table containing data ingested using Spark and you are concerned about the quality of the query plan, you must run COMPUTE STATS against such a table in any case after an ETL operation because numRows created by Spark could be incorrect. Also, use other stats computed by COMPUTE STATS, e.g., Number of Distinct Values (NDV) and NULL count for good selectivity estimates.

For example, when a user ingests data from a file into a partition of an existing table using Spark, if spark.hadoop.hive.stats.autogather is not set to false explicitly, numRows associated with this partition would be 0 even though there is at least one row in the file. To avoid this, the workaround is to set "spark.hadoop.hive.stats.autogather=false" in the "Spark Client Advanced Configuration Snippet (Safety Valve) for spark-conf/spark-defaults.conf" in Spark's CM Configuration section.