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https://issues.apache.org/jira/browse/SPARK-52762?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18036629#comment-18036629
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Dongjoon Hyun commented on SPARK-52762:
---------------------------------------
In addition, please choose one of the subtask authors ([~jonathanchang] or
[~cookiedough77]) when we assign the assignee of this issue, SPARK-52762.
Apache Spark community gives a credit to the actual contributor.
> Support analysis inside Declarative Pipelines query functions
> -------------------------------------------------------------
>
> Key: SPARK-52762
> URL: https://issues.apache.org/jira/browse/SPARK-52762
> Project: Spark
> Issue Type: Improvement
> Components: Declarative Pipelines
> Affects Versions: 4.1.0
> Reporter: Sandy Ryza
> Priority: Major
> Fix For: 4.1.0
>
>
> There are some situations where we can't resolve the relation immediately at
> the time we're registering a flow, and we need to instead communicate the
> reason and then send it later.
>
> E.g. consider this situation:
> file 1:
> ```python
> @materialized_view
> def mv1():
> data = [("Alice", 10), ("Bob", 15), ("Alice", 5)]
> return spark.createDataFrame(data, ["name", "amount"])
> ```
>
> file 2:
> ```python
> @materialized_view
> def mv2():
> return
> spark.table("mv1").groupBy("name").agg(sum("amount").alias("total_amount"))
> ```
>
> Unlike some other transformations, which get analyzed lazily, `groupBy` can
> trigger an `AnalyzePlan` Spark Connect request immediately. If the query
> function for mv2 gets executed before mv1, then it will hit an error, because
> mv1 doesn't exist yet.
>
> We can should retry it after mv1 has executed.
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