Troubleshooting Impala - Learning Cloudera Impala

Database Reference

In-Depth Information

tions are supported, so you may be trying to use an ODBC/JDBC function

that is not supported.

• The JDBC connectivity requires a specific Java Runtime depending on the

JDBC version. Because of the Java Runtime compatibility requirement with

JDBC, you must make sure that you do have a compatible Java Runtime on

a machine that is making the JDBC connection to the Impala server.

Query-specific issues

The very first query-specific issue is a bad query. The Impala query interpreter is

smart in various ways to guide you within the Impala shell for a bad query, or while

using API to execute the query statement a detailed error in the log file about it will

help you. Besides a bad query, you may also experience the following issues:

• You might use an unsupported statement or clause in your query, which will

cause a problem in query execution.

• Using an unsupported data type or a bad data transformation is another

prime reason for such issues and the resulting error or log will be helpful to

troubleshoot what went wrong.

• Sometimes the query is localized. This means that it is not distributed on oth-

er nodes. The problem could be that either the current node could not con-

nect to the other nodes due to connectivity issues, or the Impala daemon is

not running there. You will have to troubleshoot this issue by using general

connectivity troubleshooting methods between two machines. Also, make

sure Impala daemons are running with proper configuration.

• Queries could return wrong or limited results. This is possible if metadata is

not refreshed in the Impala cluster. Using the REFRESH statement, you can

sync Hive metadata to solve this problem. Also, make sure that Impala dae-

mons are running on all the nodes.

• If you find that the JOIN operations are failing, it is very mush possible that

you are hitting the memory limitation. While checking Impala logs, you might

look for Out of Memory errors logged to confirm memory limitation-specific

errors. As the JOIN operation is performed among multiple tables, which re-

quires comparatively large memory to process the JOIN request, so adding