Implement streaming versions of Dataframe.collect methods #789
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Co-authored-by: Andrew Lamb <[email protected]>
alamb
reviewed
Jul 28, 2021
datafusion/src/dataframe.rs
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| /// # Ok(()) | ||
| /// # } | ||
| /// ``` | ||
| async fn collect_stream(&self) -> Result<SendableRecordBatchStream>; |
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What if we called this something like execute rather than collect_stream?
async fn execute_stream(&self) -> Result<SendableRecordBatchStream>;
This would mirror the naming of ExecutionPlan::execute and might make it clearer that collect means collect into a Vec and execute means get a stream
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Good idea. I renamed these to execute_stream and execute_stream_partitioned
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| /// Convert the logical plan represented by this DataFrame into a physical plan and | ||
| /// execute it, collecting all resulting batches into memory while maintaining | ||
| /// partitioning | ||
| async fn collect_partitioned(&self) -> Result<Vec<Vec<RecordBatch>>> { | ||
| let state = self.ctx_state.lock().unwrap().clone(); |
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You could probably rewrite collect_partitioned to be in terms of collect_stream_partitioned:
collect(self.collect_stream_partitioned().await?)or something like that
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I've cleaned the code up and removed a fair bit of duplication now.
andygrove
changed the title
alamb
approved these changes
Jul 28, 2021
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Which issue does this PR close?
Closes #47.
Rationale for this change
In addition to the current
collect*methods that load results into memory in aVec<RecordBatch>this PR adds alternateexecute_stream*methods that return streams instead so that results don't have to be loaded into memory before being processed.What changes are included in this PR?
New
execute_streamandexecute_stream_partitionedmethods onDataFrame.Are there any user-facing changes?
Yes, new DataFrame methods.