![]() To enable CBO, navigate to Hive > Configs > Settings and find Enable Cost Based Optimizer, then switch the toggle button to On. And assigns a cost to each plan, then determines the cheapest plan to execute a query. Cost-based optimization (CBO) evaluates multiple plans to execute a query. The default value is false.īy default, Hive follows a set of rules to find one optimal query execution plan. To enable vectorized execution for the reduce side of the query, set the .enabled parameter to true. The default value is true for Hive 0.13.0 or later. To enable a vectorized query execution, navigate to the Hive Configs tab and search for the parameter. Vectorization is only applicable to the ORC file format. ![]() Vectorization directs Hive to process data in blocks of 1,024 rows rather than one row at a time. To limit the number of jobs to run in parallel, modify the .number property. Change the value to true, and then press Enter to save the value. To enable parallel query execution, navigate to the Hive Config tab and search for the property. If the independent stages can be run in parallel, that will increase query performance. The default value is 1009.Ī Hive query is executed in one or more stages. To limit the maximum number of reducers, set to an appropriate value. Given an input size of 1,024 MB, with 128 MB of data per reducer, there are eight reducers (1024/128).Īn incorrect value for the Data per Reducer parameter may result in a large number of reducers, adversely affecting query performance. Select Edit to modify the value to 128 MB (134,217,728 bytes), and then press Enter to save. To modify the parameter, navigate to the Hive Configs tab and find the Data per Reducer parameter on the Settings page. This parameter is based on your particular data requirements, compression settings, and other environmental factors. Tuning it too low could also produce too many reducers, potentially adversely affecting performance. Tuning this value down increases parallelism and may improve performance. The .per.reducer parameter specifies the number of bytes processed per reducer. With the default settings, this example is four reducers. Hive estimates the number of reducers needed as: (number of bytes input to mappers / .per.reducer). That data in ORC format with Snappy compression is 1 GB. However, Hive may have too few reducers by default, causing bottlenecks.įor example, say you have an input data size of 50 GB. Tune reducersĪpache ORC and Snappy both offer high performance. To get an optimal result, choose appropriate parameter values. These changes affect all Tez jobs across the server. Set both parameters to 33,554,432 bytes (32 MB). Expand the General panel, and locate the -size and -size parameters. To modify the limit parameters, navigate to the Configs tab of the Tez service.
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