ContextQMD
Back to Datafusion

Extending Operators

docs/source/library-user-guide/extending-operators.md

53.1.03.2 KB
Original Source
<!--- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. -->

Extending Operators

DataFusion supports extending operators by transforming LogicalPlan and ExecutionPlan through customized optimizer rules. This section will use the µWheel project to illustrate such capabilities.

About DataFusion µWheel

DataFusion µWheel is a native DataFusion optimizer which improves query performance for time-based analytics through fast temporal aggregation and pruning using custom indices. The integration of µWheel into DataFusion is a joint effort with the DataFusion community.

Optimizing Logical Plan

The rewrite function transforms logical plans by identifying temporal patterns and aggregation functions that match the stored wheel indices. When match is found, it queries the corresponding index to retrieve pre-computed aggregate values, stores these results in a MemTable, and returns as a new LogicalPlan::TableScan. If no match is found, the original plan proceeds unchanged through DataFusion's standard execution path.

rust,ignore
fn rewrite(
  &self,
  plan: LogicalPlan,
  _config: &dyn OptimizerConfig,
) -> Result<Transformed<LogicalPlan>> {
    // Attempts to rewrite a logical plan to a uwheel-based plan that either provides
    // plan-time aggregates or skips execution based on min/max pruning.
    if let Some(rewritten) = self.try_rewrite(&plan) {
        Ok(Transformed::yes(rewritten))
    } else {
        Ok(Transformed::no(plan))
    }
}
rust,ignore
// Converts a uwheel aggregate result to a TableScan with a MemTable as source
fn agg_to_table_scan(result: f64, schema: SchemaRef) -> Result<LogicalPlan> {
  let data = Float64Array::from(vec![result]);
  let record_batch = RecordBatch::try_new(schema.clone(), vec![Arc::new(data)])?;
  let df_schema = Arc::new(DFSchema::try_from(schema.clone())?);
  let mem_table = MemTable::try_new(schema, vec![vec![record_batch]])?;
  mem_table_as_table_scan(mem_table, df_schema)
}

To get a deeper dive into the usage of the µWheel project, visit the blog post by Max Meldrum.