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+---
+layout: post
+title: "DataFusion Now Supports Substrait"
+date: "2023-02-27 00:00:00"
+author: "pmc"
+categories: [arrow]
+---
+
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+
+## Introduction
+
+The Apache Arrow PMC is pleased to announce that the DataFusion project has accepted the donation of the
+datafusion-substrait crate, which was developed by the DataFusion community under the
+[datafusion-contrib](https://github.com/datafusion-contrib/) GitHub organization.
+
+Substrait provides a standardized representation of query plans and expressions. In many ways, the project's goal
+is similar to that of the Arrow project. Arrow standardizes the memory representation of columnar data. Substrait
+standardizes the representation of operations on data, such as filter and query plans.
+
+Now that DataFusion can directly run Substrait query plans, there are several exciting new integration possibilities:
+
+- Pass serialized query plan across language boundaries, such as passing from Python to Rust or Rust to C++. For
+  , a Python based SQL frontend could pass a Substrait plan to DataFusion which is written in Rust.
+- Mixing and matching query engine front-ends and back-ends based on their specific strengths. For example, using
+  DataFusion for query planning, and Velox for execution, or Calcite for query planning and DataFusion for execution.
+- Easier integration for other DataFusion based projects. For example, the related Ballista project, which already
+  provides “distributed DataFusion” execution plans, serializes query plans using a protobuf format that predates
+  the Substrait project. By adopting Substrait, Ballista can provide distributed scheduling for query engines
+  other than DataFusion.
+
+## Logical Plan Support
+
+DataFusion currently supports serialization and deserialization of the following logical operators and expressions with Substrait.
+
+### Operators / Relations
+
+| DataFusion    | SQL                     | DataFusion Supported Subtypes           |
+| ------------- | ----------------------- | --------------------------------------- |
+| Projection    | SELECT                  |                                         |
+| TableScan     | FROM                    |                                         |
+| Filter        | WHERE                   |                                         |
+| Aggregate     | GROUP BY                |                                         |
+| Sort          | ORDER BY                |                                         |
+| Join          | JOIN                    | LEFT, RIGHT, FULL, LEFT ANTI, LEFT SEMI |
+| Limit         | LIMIT                   |                                         |
+| Distinct      | DISTINCT                |                                         |
+| SubqueryAlias | \<subquery> AS \<alias> |                                         |
+
+### Expressions
+
+| DataFusion        | SQL                         | DataFusion Supported Subtypes                                                                                  |
+| ----------------- | --------------------------- | -------------------------------------------------------------------------------------------------------------- | ----- | ----- | ----- | ---------- |
+| AggregateFunction |                             |                                                                                                                |
+| Alias             | \<expr> AS \<alias>         |                                                                                                                |
+| Column            | \<identifier>               |                                                                                                                |
+| BinaryExpr        | \<expr>                     |                                                                                                                |
+| Between           | BETWEEN \<expr> AND \<expr> |                                                                                                                |
+| Case              | CASE ... WHEN ... END       |                                                                                                                |
+| Literal           |                             | Int8, Int16, Int32, Int64, Boolean, Float32, Float64, Decimal128, Utf8, LargeUtf8, Binary, LargeBinary, Date32 |
+| Literal Null      |                             | Int8                                                                                                           | Int16 | Int32 | Int64 | Decimal128 |
+
+## Physical Plan Support
+
+There is also preliminary work on supporting serialization of physical plans. The tracking issue for this is
+[#5173](https://github.com/apache/arrow-datafusion/issues/5173).
+
+## Python Bindings
+
+Substrait support is also available from DataFusion’s [Python bindings](https://github.com/apache/arrow-datafusion-python/).
+
+Source code for this example is available [here](https://github.com/apache/arrow-datafusion-python/blob/main/examples/substrait.py).
+
+```python
+from datafusion import SessionContext
+from datafusion import substrait as ss
+
+# Create a DataFusion context
+ctx = SessionContext()
+
+# Register table with context
+ctx.register_parquet('aggregate_test_data', './testing/data/csv/aggregate_test_100.csv')
+
+substrait_plan = ss.substrait.serde.serialize_to_plan("SELECT * FROM aggregate_test_data", ctx)
+# type(substrait_plan) -> <class 'datafusion.substrait.plan'>
+
+# Alternative serialization approaches
+# type(substrait_bytes) -> <class 'list'>, at this point the bytes can be distributed to file, network, etc safely
+# where they could subsequently be deserialized on the receiving end.
+substrait_bytes = ss.substrait.serde.serialize_bytes("SELECT * FROM aggregate_test_data", ctx)
+
+# Imagine here bytes would be read from network, file, etc ... for example brevity this is omitted and variable is simply reused
+# type(substrait_plan) -> <class 'datafusion.substrait.plan'>
+substrait_plan = ss.substrait.serde.deserialize_bytes(substrait_bytes)
+
+# type(df_logical_plan) -> <class 'substrait.LogicalPlan'>
+df_logical_plan = ss.substrait.consumer.from_substrait_plan(ctx, substrait_plan)
+
+# Back to Substrait Plan just for demonstration purposes
+# type(substrait_plan) -> <class 'datafusion.substrait.plan'>
+substrait_plan = ss.substrait.producer.to_substrait_plan(df_logical_plan)
+```
+
+## Availability
+
+Substrait support is available in DataFusion 18.0.0 and version 0.8.0 of the Python bindings.
+
+## Get Involved
+
+The Substrait support is at an early stage of development, and we would welcome more contributors to expand the
+functionality and to help with compatibility testing with other data infrastructure that supports Substrait.
+
+If you are interested in getting involved, an excellent place to start is to read our
+[communication](https://arrow.apache.org/datafusion/contributor-guide/communication.html) and
+[contributor](https://arrow.apache.org/datafusion/contributor-guide/index.html) guides.