[SPARK- 52810][SDP][SQL] Spark Pipelines CLI Selection Options #51507

JiaqiWang18 · 2025-07-16T01:27:05Z

What changes were proposed in this pull request?

We want to give user the ability to choose a subset of datasets (ex: tables, materialized views) to include in a run.
And the ability to specify if they should ran as regular refresh or full refresh.
Below arguments being added to the spark-pipelines CLI to achieve this

--full-refresh: List of datasets to reset and recompute.

--full-refresh-all: Boolean, whether to perform a full graph reset and recompute.

--refresh: List of datasets to update.

If no options are specified, the default is to perform a refresh for all datasets in the pipeline.

To enable above:

new CLI options are added to the python CLI
proto changes are made to allow passing them to spark
changes in spark pipelines codebase to use TableFilter to control graph refresh

Why are the changes needed?

These changes are needed because we want to give users option to control what to run and how to run for their pipelines.

Does this PR introduce any user-facing change?

Yes, new CLI options are being added. However, SDP haven't been released yet so no user should be impacted.

How was this patch tested?

Added new test suite in the python CLI to verify argument parsing.
Added new test suite in scala codebase to use the newly added CLI options to run a full pipeline to verify behavior.

Was this patch authored or co-authored using generative AI tooling?

No

JiaqiWang18 · 2025-07-16T18:02:08Z

@AnishMahto

JiaqiWang18 · 2025-07-16T18:42:21Z

@sryza

AnishMahto

Flushing out some thoughts! Haven't looked at tests yet.

AnishMahto · 2025-07-16T19:56:57Z

python/pyspark/pipelines/cli.py

+    if full_refresh_all:
+        if full_refresh:
+            raise PySparkException(
+                errorClass="CONFLICTING_PIPELINE_REFRESH_OPTIONS", messageParameters={}


Thoughts on having sub error classes for mismatched combinations? Or maybe just pass along which two configs are conflicting as a message parameter?

Added logic to pass along the conflicting option

AnishMahto · 2025-07-16T20:03:27Z

python/pyspark/pipelines/cli.py

+    result = []
+    for table_list in table_lists:
+        result.extend(table_list)
+    return result if result else None


If result is an empty list, do we still want to return None? Or should we just return the empty list? What is the implication of either here

Removed this by using the extend option in arg parser to avoid creating nested list.

AnishMahto · 2025-07-16T20:05:57Z

python/pyspark/pipelines/cli.py

+        "--full-refresh",
+        type=parse_table_list,
+        action="append",
+        help="List of datasets to reset and recompute (comma-separated).",


Here and below, should we document default behavior if this arg is not specified at all?

Will extend split using commas?

AnishMahto · 2025-07-16T20:11:43Z

python/pyspark/pipelines/cli.py

-        run(spec_path=spec_path)
+        run(
+            spec_path=spec_path,
+            full_refresh=flatten_table_lists(args.full_refresh),


Why do we need to flatten args.full_refresh and args.refresh? I thought we defined their types with the parse_table_list function, which returns List[str]

This is for the case if user provide the same args multiple times.
Ex: (--full_refresh: "a,b" --full_refresh: "c,d"). Then we will receive a nested list [["a","b"],["c"]]. Need to perform a flattening to transform it into a 1D list.

Ah got it, makes sense

If we were to mark this argument field as extend rather than append, would we still need to do any manual flattening?

Very good point, extend creates a 1D list directly.

python/pyspark/pipelines/spark_connect_pipeline.py

sql/connect/common/src/main/protobuf/spark/connect/pipelines.proto

sql/connect/server/src/main/scala/org/apache/spark/sql/connect/pipelines/PipelinesHandler.scala

AnishMahto · 2025-07-16T20:49:23Z

sql/connect/server/src/main/scala/org/apache/spark/sql/connect/pipelines/PipelinesHandler.scala

      sessionHolder: SessionHolder): Unit = {
    val dataflowGraphId = cmd.getDataflowGraphId
    val graphElementRegistry = DataflowGraphRegistry.getDataflowGraphOrThrow(dataflowGraphId)
+


Can we extract all this added logic to deduce the full refresh and regular refresh table filters into its own function? And then as part of the scala docs, map the expected filter results depending on what combination of full refresh and partial refresh is selected

extracted a createTableFilters function

...ipelines/src/main/scala/org/apache/spark/sql/pipelines/graph/PipelineUpdateContextImpl.scala

AnishMahto · 2025-07-16T21:04:38Z

sql/connect/server/src/main/scala/org/apache/spark/sql/connect/pipelines/PipelinesHandler.scala

+    if (refreshTables.nonEmpty && fullRefreshTables.nonEmpty) {
+      // check if there is an intersection between the subset
+      val intersection = refreshTableNames.intersect(fullRefreshTableNames)
+      if (intersection.nonEmpty) {
+        throw new IllegalArgumentException(
+          "Datasets specified for refresh and full refresh cannot overlap: " +
+            s"${intersection.mkString(", ")}")
+      }
+    }
+
+    val fullRefreshTablesFilter: TableFilter = if (fullRefreshAll) {
+      AllTables
+    } else if (fullRefreshTables.nonEmpty) {
+      SomeTables(fullRefreshTableNames)
+    } else {
+      NoTables
+    }
+
+    val refreshTablesFilter: TableFilter =
+      if (refreshTables.nonEmpty) {
+        SomeTables(refreshTableNames)
+      } else if (fullRefreshTablesFilter != NoTables) {
+        NoTables
+      } else {
+        AllTables
+      }


just an optional nit, but as a code reader it's difficult for me to reason about the combinations of fullRefreshTables and refreshTables when reading them as sequential but related validation here.

My suggestion would be to restructure this as a match statement, that explicitly handles each combination. Ex.

(fullRefreshTables, refreshTableNames) match { case (Nil, Nil) => ... case (fullRefreshTables, Nil) => ... case ... }

extracted a createTableFilters function

sryza · 2025-07-16T21:03:27Z

python/pyspark/pipelines/cli.py

 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any, Generator, Mapping, Optional, Sequence
+from typing import Any, Generator, Mapping, Optional, Sequence, List


Out of alphabetical order: you may need to run dev/reformat-python to format this.

actually it didn't reformat this but I manually reordered it

python/pyspark/pipelines/cli.py

sryza · 2025-07-16T21:17:07Z

python/pyspark/pipelines/cli.py


-def run(spec_path: Path) -> None:
-    """Run the pipeline defined with the given spec."""
+def run(


If we expect it to vary across run for the same pipeline, it should be a CLI arg. If we expect it to be static for a pipeline, it should live in the spec. I would expect selections to vary across runs.

python/pyspark/pipelines/spark_connect_pipeline.py

sryza · 2025-07-16T21:23:10Z

python/pyspark/pipelines/tests/test_cli.py

+    not should_test_connect or not have_yaml,
+    connect_requirement_message or yaml_requirement_message,
+)
+class CLIValidationTests(unittest.TestCase):


Is there a meaningful difference between the kinds of tests that are included in this class and the kinds of tests that included in the other class in this file?

yeah I think they can be combined into one.

.../test/scala/org/apache/spark/sql/connect/pipelines/SparkDeclarativePipelinesServerTest.scala

...r/src/test/scala/org/apache/spark/sql/connect/pipelines/PipelineRefreshFunctionalSuite.scala

sryza

LGTM!

sryza · 2025-07-17T19:44:36Z

Merged to master

…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 <[email protected]> Signed-off-by: Dongjoon Hyun <[email protected]>

jackywang-db added 9 commits July 14, 2025 15:37

cli args

b24698c

working 1 test

1d6ec2c

2 test pass

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more tests

7fbe8e7

add server side validation

109de10

add validation tests

7e990c5

python cli tests

e494a57

modify backend tests

4105c97

test overhaul

e580bb4

github-actions bot added SQL PYTHON CONNECT labels Jul 16, 2025

jackywang-db added 4 commits July 15, 2025 20:42

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JiaqiWang18 changed the title ~~[WIP][SPARK- 52810][SDP][SQL] Spark Pipelines CLI Selection Options~~ [SPARK- 52810][SDP][SQL] Spark Pipelines CLI Selection Options Jul 16, 2025

AnishMahto reviewed Jul 16, 2025

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sryza reviewed Jul 16, 2025

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jackywang-db added 4 commits July 16, 2025 21:39

address feedback

1693ac5

rename proto

e56d39b

fmt

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nit

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JiaqiWang18 requested review from AnishMahto and sryza July 17, 2025 18:26

sryza approved these changes Jul 17, 2025

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sryza closed this in 9204b05 Jul 17, 2025

dongjoon-hyun mentioned this pull request Oct 1, 2025

[SPARK-53777] Update Spark Connect-generated Swift source code with 4.1.0-preview2 apache/spark-connect-swift#250

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[SPARK- 52810][SDP][SQL] Spark Pipelines CLI Selection Options #51507

[SPARK- 52810][SDP][SQL] Spark Pipelines CLI Selection Options #51507

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JiaqiWang18 commented Jul 16, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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What changes were proposed in this pull request?

Why are the changes needed?

Does this PR introduce any user-facing change?

How was this patch tested?

Was this patch authored or co-authored using generative AI tooling?

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JiaqiWang18 commented Jul 16, 2025

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sryza commented Jul 17, 2025

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