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How this milestone will help users to play with Storm SQL?
- Users can run 'explain' to see query plan for DML statement before submitting Trident topology.
- Users can use GROUP BY and JOIN statement in DML statement
- Note that these feature follows the Trident semantic of aggregation and join
- Aggregation is done within batch
- SQE does stateful aggregation, so Storm SQL might follow later
- Join is done with each of batches
- But respecting Streaming SQL semantic seems correct, which means that we could get rid of these features again and wait for Streaming SQL
- This is what Flink is doing, but Flink have Table API so Flink can support window aggregation and join without Calcite support
- Users can run Storm SQL Users will be able to run Storm SQL Runner without copying dependencies to extlib.
- This is resolved from
but this issue was originally came fromJira server ASF JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId 5aa69414-a9e9-3523-82ec-879b028fb15b key STORM-2016 Jira server ASF JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId 5aa69414-a9e9-3523-82ec-879b028fb15b key STORM-1435
- This is resolved from
- Users will be able to use GROUP BY and JOIN statement in DML statement
- Note that these feature follows the Trident semantic of aggregation and join
- Aggregation is done within batch
- SQE does stateful aggregation, so Storm SQL might follow later
- Join is done with each of batches
- But respecting Streaming SQL semantic seems correct, which means that we could get rid of these features again and wait for Streaming SQL
- This is what Flink is doing, but Flink have Table API so Flink can support window aggregation and join without Calcite support
- Users will be able to Users can use user defined aggregate function in Trident mode.
- User defined function is already supported
- Users will be able to run 'explain' to see query plan for DML statement before submitting Trident topology
- Users will be able to Users can specify parallelism of input data source which will be used unless repartitioning is made
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