[SPARK-52449][CONNECT][PYTHON][ML] Make datatypes for Expression.Literal.Map/Array optional#51473
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[SPARK-52449][CONNECT][PYTHON][ML] Make datatypes for Expression.Literal.Map/Array optional#51473heyihong wants to merge 1 commit into
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cc @zhengruifeng too |
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friendly ping @hvanhovell @HyukjinKwon @beliefer @zhengruifeng @WeichenXu123 Update: No need to review at the moment — I need to finish SPARK-52930 first. |
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what is the diff here? why it changed the analyzed plan?
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@zhengruifeng The diff is caused by an extra test case I added:
fn.typedLit(
Seq(
mutable.LinkedHashMap("a" -> Seq("1", "2"), "b" -> Seq("3", "4")),
mutable.LinkedHashMap("a" -> Seq("5", "6"), "b" -> Seq("7", "8")),
mutable.LinkedHashMap("a" -> Seq.empty[String], "b" -> Seq.empty[String])))[keys: [a,b], values: [[1,2],[3,4]],keys: [a,b], values: [[5,6],[7,8]],keys: [a,b], values: [[],[]]] AS ARRAY(MAP('a', ARRAY('1', '2'), 'b', ARRAY('3', '4')), MAP('a', ARRAY('5', '6'), 'b', ARRAY('7', '8')), MAP('a', ARRAY(), 'b', ARRAY()))#0
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@heyihong please resolve the conflicts |
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…teral.Array optional
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merged to master |
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…th `4.1.0-preview2` ### What changes were proposed in this pull request? This PR aims to update Spark Connect-generated Swift source code with Apache Spark `4.1.0-preview2`. ### Why are the changes needed? There are many changes from Apache Spark 4.1.0. - apache/spark#52342 - apache/spark#52256 - apache/spark#52271 - apache/spark#52242 - apache/spark#51473 - apache/spark#51653 - apache/spark#52072 - apache/spark#51561 - apache/spark#51563 - apache/spark#51489 - apache/spark#51507 - apache/spark#51462 - apache/spark#51464 - apache/spark#51442 To use the latest bug fixes and new messages to develop for new features of `4.1.0-preview2`. ``` $ git clone -b v4.1.0-preview2 https://github.com/apache/spark.git $ cd spark/sql/connect/common/src/main/protobuf/ $ protoc --swift_out=. spark/connect/*.proto $ protoc --grpc-swift_out=. spark/connect/*.proto // Remove empty GRPC files $ cd spark/connect $ grep 'This file contained no services' * catalog.grpc.swift:// This file contained no services. commands.grpc.swift:// This file contained no services. common.grpc.swift:// This file contained no services. example_plugins.grpc.swift:// This file contained no services. expressions.grpc.swift:// This file contained no services. ml_common.grpc.swift:// This file contained no services. ml.grpc.swift:// This file contained no services. pipelines.grpc.swift:// This file contained no services. relations.grpc.swift:// This file contained no services. types.grpc.swift:// This file contained no services. $ rm catalog.grpc.swift commands.grpc.swift common.grpc.swift example_plugins.grpc.swift expressions.grpc.swift ml_common.grpc.swift ml.grpc.swift pipelines.grpc.swift relations.grpc.swift types.grpc.swift ``` ### Does this PR introduce _any_ user-facing change? Pass the CIs. ### How was this patch tested? Pass the CIs. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #250 from dongjoon-hyun/SPARK-53777. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
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Nov 25, 2025
…ral.Map/Array optional ### What changes were proposed in this pull request? This PR optimizes the `LiteralValueProtoConverter` to reduce redundant type information in Spark Connect protocol buffers. The key changes include: 1. **Optimized type inference for arrays and maps**: Modified the conversion logic to only include type information in the first element of arrays and the first key-value pair of maps, since subsequent elements can infer their types from the first element. 2. **Added `needDataType` parameter**: Introduced a new parameter to control when type information is necessary, allowing the converter to skip redundant type information. 3. **Updated protobuf documentation**: Enhanced comments in the protobuf definitions to clarify that only the first element needs to contain type information for inference. 4. **Improved test coverage**: Added new test cases for complex nested structures including tuples and maps with array values. ### Why are the changes needed? The current implementation includes type information for every element in arrays and every key-value pair in maps, which is redundant and increases the size of protocol buffer messages. Since Spark Connect can infer types from the first element, including type information for subsequent elements is unnecessary and wastes bandwidth and processing time. ### Does this PR introduce any user-facing change? **No** - This PR does not introduce any user-facing changes. The change is backward compatible and existing connect clients will continue to work unchanged. ### How was this patch tested? `build/sbt "connect/testOnly *LiteralExpressionProtoConverterSuite"` ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Cursor 1.4.5 Closes apache#51473 from heyihong/SPARK-52449. Authored-by: Yihong He <heyihong.cn@gmail.com> Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
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What changes were proposed in this pull request?
This PR optimizes the
LiteralValueProtoConverterto reduce redundant type information in Spark Connect protocol buffers. The key changes include:Optimized type inference for arrays and maps: Modified the conversion logic to only include type information in the first element of arrays and the first key-value pair of maps, since subsequent elements can infer their types from the first element.
Added
needDataTypeparameter: Introduced a new parameter to control when type information is necessary, allowing the converter to skip redundant type information.Updated protobuf documentation: Enhanced comments in the protobuf definitions to clarify that only the first element needs to contain type information for inference.
Improved test coverage: Added new test cases for complex nested structures including tuples and maps with array values.
Why are the changes needed?
The current implementation includes type information for every element in arrays and every key-value pair in maps, which is redundant and increases the size of protocol buffer messages. Since Spark Connect can infer types from the first element, including type information for subsequent elements is unnecessary and wastes bandwidth and processing time.
Does this PR introduce any user-facing change?
No - This PR does not introduce any user-facing changes.
The change is backward compatible and existing connect clients will continue to work unchanged.
How was this patch tested?
build/sbt "connect/testOnly *LiteralExpressionProtoConverterSuite"Was this patch authored or co-authored using generative AI tooling?
Generated-by: Cursor 1.4.5