Data Query Tips and Tricks

See Intermediate Results My Data Query

When creating a data query, the good practice is to put a RESULT SET operator after each operator. Verify that what comes out of the preceding operator is conform to your expectations. Once the output is good, you can remove the RESULT SET operator.

Make Aggregations

You can make aggregations at several levels with several methods.

#	Method	Description
1	AGGREGATE transformation operator	You can use AGGREGATE operators in the data query. However: This can make your data query more complex if you want to perform several aggregations. You cannot reuse these aggregations at the visualization level. Recommendation: Avoid adding multiple AGGREGATE operators.
2	Result Set terminal operator	You can define several aggregations in a Result Set at the end of the data query. This is very useful to declare several aggregations once and use them for several visualizations at the visualization level. Recommendation: Choose this method to mutualize your aggregation definitions.
3	Aggregation at the visualization level	You can specify an aggregation in the Visualization Properties panel, from the Measures section. This is useful if the aggregation is specific to the visualization. Tip: To use a same aggregation in several visualizations, it is better to declare it at the Result Set level.

Use Item Instead of Tuples

With the Semantic Graph Index, it is better to manipulate items rather than tuples, for performance reasons. That is why it is better to keep item objects as close as possible to the end of the data query. It is therefore different from SQL, where you typically transform items in Tuples to reduce the number of attributes.

The following use case shows how you would proceed in SQL, and how to do it more efficiently in Semantic Graph Index.

To reproduce an SQL query, you would add the MAP with its item objects at the beginning of the query.

In Data Perspective Studio data queries, avoid adding tuple transformation as in SQL. In SQL, you choose only the interesting columns and make transformations.

In Data Perspective Studio data queries, try to put the MAP operator and object items at the end of the chain. The goal is to make the transformation as close as possible to the output.

Enhance the Data Query Performance

When you Run your data query configuration, you can use the Profile debugging tool.

Important: Under Params, enter your input parameters, if any.

When you click Profile, you get a view with several tabs.

The Summary tab lists all potential issues.

The Logical plan tab shows the CPU usage per thread and the Memory Usage.

Tips: If you zoom in the Graph view, you can see icons indicating operator issues that may have an impact on performance. For example, flame icons represent heavy CPU consumption, elephant icons represent heavy memory consumption. You can also see the number of objects coming out of the operators.