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https://issues.apache.org/jira/browse/SPARK-45876?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17786192#comment-17786192
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Alexander Petrossian (PAF) commented on SPARK-45876:
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After making ReturnAnswer and Generate transparent to collectProjectsAndFilters
(copy/pasted ResolvedHint approach), plan looks good:
{code:java}
(1) Scan orc
Output [1]: [data#0]
Batched: true
Location: InMemoryFileIndex
[file:/Users/paf/Documents/Hermes/EDR/spark-tests/MAJOR-2023-11-07.HERMES.orc]
PushedFilters: [IsNotNull(frelatedparty), IsNotNull(resource.id),
IsNotNull(resource.value), EqualTo(resource.id,MSISDN),
EqualTo(resource.value,79626786937)] {code}
But does not work, .show() fails:
{code:java}
java.lang.IllegalStateException: Couldn't find feventitem#13 in [data#0] {code}
> Filters are not pushed down across lateral view
> -----------------------------------------------
>
> Key: SPARK-45876
> URL: https://issues.apache.org/jira/browse/SPARK-45876
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.5.0
> Reporter: Alexander Petrossian (PAF)
> Priority: Major
> Attachments: Снимок экрана 2023-11-14 в 16.33.48.png, Снимок экрана
> 2023-11-14 в 16.35.56.png, Снимок экрана 2023-11-14 в 16.55.11.png, Снимок
> экрана 2023-11-14 в 16.55.31.png, Снимок экрана 2023-11-14 в 16.58.56.png
>
>
> {code:python}
> from pyspark.sql import SparkSession
> spark = SparkSession.builder.config("spark.sql.catalogImplementation",
> "hive").appName("Write ORC File").getOrCreate()
> spark.sql('drop TABLE if exists test').show()
> spark.sql('CREATE EXTERNAL TABLE test (request
> struct<characteristic:array<struct<id:string,value:string>>>)'
> 'ROW FORMAT SERDE "org.apache.hadoop.hive.ql.io.orc.OrcSerde" '
> 'STORED AS INPUTFORMAT "org.apache.hadoop.hive.ql.io.orc.OrcInputFormat" '
> 'OUTPUTFORMAT "org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat" '
> 'LOCATION "testfolder"').show()
> spark.sql("select request from test lateral view
> explode(request.characteristic) cTable as c where
> c.value='79640000000'").explain()
> {code}
> shows
> {code}
> == Physical Plan ==
> *(1) Project [request#2]
> +- *(1) Filter (isnotnull(c#4.value) AND (c#4.value = 79640000000))
> +- *(1) Generate explode(request#2.characteristic), [request#2], false,
> [c#4]
> +- *(1) ColumnarToRow
> +- FileScan orc spark_catalog.default.test[request#2] Batched: true,
> DataFilters: [], Format: ORC, Location: InMemoryFileIndex(1
> paths)[file:/Users/paf/Downloads/spark-warehouse/testfolder],
> PartitionFilters: [], PushedFilters: [], ReadSchema:
> struct<request:struct<characteristic:array<struct<id:string,value:string>>>>
> {code}
> Which is extremely slow.
> Suppose I search for a column value, which is totally out of min/max
> statistics range.
> Search could have been much faster, but no.
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