Flow Optimization Settings Dialog
In the Flow Optimization Settings dialog, you can configure the following settings, which provide finer-grained control and performance tuning over your flow and its job executions. From the Flow View menu, select Optimization settings.
This feature must be enabled at the workspace level. When enabled, the settings in this dialog are applied to the current flow.
These optimizations are designed to improve performance by pre-filtering the volume of data by reducing the columns and rows to the ones that are actually used.
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In general, all of these optimizations should be enabled for each flow. As needed, you can selectively disable optimizations if you are troubleshooting execution issues.
When these filters are enabled, the number of filters successfully applied to a job execution is listed in the Optimization summary in the Job Details page. See Job Details Page.
Enable optimization for jobs from this flow
When enabled, the Cloud Portal attempts to apply any of the listed optimizations that are enabled to jobs that are executed for this flow.
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When thisoption is disabled, then no optimization settings are available.
General Optimizations
The following optimizations can be enabled or disabled in general. For individual data sources, you may be able to enable or disable these settings based on your environment and its requirements.
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These optimizations are applied at the recipe level. They can be applied on any flow and may improve performance within the Transformer page.
Column pruning optimization
When enabled, job execution performance is improved by removing any unused or redundant columns based on the recipe that is selected.
Filter optimization
When this setting is enabled, the Cloud Portal optimizes job performance on this flow by pushing data filters to recipes.
Other optimizations
Additional optimizations can be enabled or disabled for specific types of transformations or jobs.
File-Based Optimizations
Databases that Support Pushdown
Individual types of databases may support one or more of the following pushdowns. Additional restrictions may apply for your specific database.
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These optimizations are applied to queries of your relational datasources that support pushdown. These optimizations are applied within the source, which limits the volume of data that is transferred during job execution.
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For each relational connection, you can enable the optimization capabilities to improve the flow and its job execution performance. The optimization settings may vary based on the type of relational connections.
Column pruning from source
When enabled, job execution performance is improved by removing any unused or redundant columns from the source database.
Limitations:
Column pruning optimizations cannot be applied to imported datasets generated with custom SQL.
Filter pushdown
When this setting is enabled, the Cloud Portal optimizes job performance on this flow by pushing data filters directly on the source database.
Limitations:
Filter pushdown optimizations cannot be applied to imported datasets generated with custom SQL.
Pushdown filters cannot be applied to dates in your relational sources.
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SQL-based filtering is performed on a best-effort basis. When these optimizations are enabled for your flow, there is no guarantee that they will be applied during job execution.
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The connection types may or may not be available in your product edition. For more information, see Connection Types.
Sample pushdown
When this setting is enabled, the Cloud Portal optimizes job performance by executing sampling jobs directly on the source database.
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All pushdowns must be enabled to ensure sample jobs run in the database.
Snowflake pushdown options
In addition to common database options, the following flow optimization options are available for Snowflake.
Source to Files
When enabled, Snowflake tables that meet all pushdown requirements can be executed in Snowflake and published to files.
Limitations:
AVRO file formats are not supported.
For single-file publishing, only 5 GB limit is supported.
For more information on executing jobs in Snowflake, see Snowflake Running Environment.
Other Databases
Databases that do not support pushdown may support the following optimization settings.
Column pruning from source
When enabled, job execution performance is improved by removing any unused or redundant columns from the source database.