Member since
10-25-2014
111
Posts
4
Kudos Received
2
Solutions
My Accepted Solutions
Title | Views | Posted |
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127 | 10-06-2024 12:35 PM | |
4903 | 11-14-2014 06:24 PM |
10-08-2024
04:27 PM
1 Kudo
Hello- Impala is architected for querying "large datasets" out of the box. However, depending on your requirements, you need to allocate enough hardware and resources. You can start with https://impala.apache.org/docs/build/html/topics/impala_scalability.html, https://impala.apache.org/docs/build/html/topics/impala_resource_management.html, https://impala.apache.org/docs/build/html/topics/impala_performance.html, and https://impala.apache.org/docs/build/html/topics/impala_planning.html. Let me know if that helps.
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10-07-2024
07:52 AM
Sure, it’s the latest version available. We have opened a case to cloudera, but being Impala and python widely used together I am surprised not finding lots bug report about this.
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10-06-2024
12:27 PM
1 Kudo
Hello- See https://docs.cloudera.com/documentation/other/connectors/impala-jdbc/2-6-23/Cloudera-JDBC-Driver-for-Impala-Install-Guide.pdf for instructions on how to configure JAAS for JDBC. P.16, for example. Also -- just search for 'JAAS' the whole document, and follow the steps, as applicable.
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10-03-2024
11:52 AM
Hello- First of all, make sure you are using the latest Impala JDBC connector. If you do - then try to add 'UseNativeQuery=1' to the JDBC connection string and re-test.
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10-03-2024
11:33 AM
Hello- Make sure first of all you are using the latest Cloudera JDBC.
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10-03-2024
11:04 AM
Hello- Seems like a file is missing: the code is trying to open a file, but it is not there: return Popen(*popenargs, **kwargs).wait() Also the following seems relevant to how make Python more explicit: https://stackoverflow.com/questions/8978057/raising-builtin-exception-with-default-message-in-python
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06-02-2016
10:30 AM
I worked with Cloudera support and they found a solution The issue This issue is caused by the HiveServer2 failing to execute a MapReduce Local Task and it does not seem bound to queries submitted through ODBC The solution In the ODBC properties I set hive.auto.convert.join to false
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