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[SPARK-19893][SQL] should not run DataFrame set oprations with map type #17236
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Test build #74300 has started for PR 17236 at commit |
retest this please |
@@ -319,7 +322,7 @@ trait CheckAnalysis extends PredicateHelper { | |||
// Check if the data types match. | |||
dataTypes(child).zip(ref).zipWithIndex.foreach { case ((dt1, dt2), ci) => | |||
// SPARK-18058: we shall not care about the nullability of columns | |||
if (TypeCoercion.findWiderTypeForTwo(dt1.asNullable, dt2.asNullable).isEmpty) { | |||
if (!dt1.sameType(dt2)) { |
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We shouldn't change this. This makes sure we generate the correct error message for union. The problem is that an earlier pair of columns might not be the same but castable, while a later pair column is not the same and we can't cast them; the error should show the latter pair of columns and not the first one (which happens if we revert this).
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See #16882 for more information.
@cloud-fan can we also check |
Test build #74309 has finished for PR 17236 at commit
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LGTM pending jenkins |
Test build #74316 has finished for PR 17236 at commit
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Test build #74317 has finished for PR 17236 at commit
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val e2 = intercept[AnalysisException](df.except(df)) | ||
assert(e2.message.contains( | ||
"Cannot have map type columns in DataFrame which calls intersect/except/distinct")) | ||
val e3 = intercept[AnalysisException](df.distinct()) |
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For some reason I don't understand, the code path for df.distinct() actually creates an aggregate, whereas the SQL code path uses the Distinct
operator. So we need to actually issue a sql statement here.
Test build #74329 has finished for PR 17236 at commit
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Test build #74343 has finished for PR 17236 at commit
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thanks for the review, merging to master! |
In spark SQL, map type can't be used in equality test/comparison, and `Intersect`/`Except`/`Distinct` do need equality test for all columns, we should not allow map type in `Intersect`/`Except`/`Distinct`. new regression test Author: Wenchen Fan <wenchen@databricks.com> Closes #17236 from cloud-fan/map. (cherry picked from commit fb9beda) Signed-off-by: Wenchen Fan <wenchen@databricks.com>
In spark SQL, map type can't be used in equality test/comparison, and `Intersect`/`Except`/`Distinct` do need equality test for all columns, we should not allow map type in `Intersect`/`Except`/`Distinct`. new regression test Author: Wenchen Fan <wenchen@databricks.com> Closes #17236 from cloud-fan/map. (cherry picked from commit fb9beda) Signed-off-by: Wenchen Fan <wenchen@databricks.com>
backported to 2.1/2.0 |
@cloud-fan I think branch 2.0 fails after this commit unfortunately, such as in
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I'm pretty sorry about this, I have fixed it in branch-2.0, @srowen thanks for pointing this out! |
@cloud-fan @yhuai @sameeragarwal @hvanhovell Any plan to re-enable |
### What changes were proposed in this pull request? `hash()` and `xxhash64()` cannot be used on elements of `Maptype`. A new configuration `spark.sql.legacy.useHashOnMapType` is introduced to allow users to restore the previous behaviour. When `spark.sql.legacy.useHashOnMapType` is set to false: ``` scala> spark.sql("select hash(map())"); org.apache.spark.sql.AnalysisException: cannot resolve 'hash(map())' due to data type mismatch: input to function hash cannot contain elements of MapType; line 1 pos 7; 'Project [unresolvedalias(hash(map(), 42), None)] +- OneRowRelation ``` when `spark.sql.legacy.useHashOnMapType` is set to true : ``` scala> spark.sql("set spark.sql.legacy.useHashOnMapType=true"); res3: org.apache.spark.sql.DataFrame = [key: string, value: string] scala> spark.sql("select hash(map())").first() res4: org.apache.spark.sql.Row = [42] ``` ### Why are the changes needed? As discussed in Jira, SparkSql's map hashcodes depends on their order of insertion which is not consistent with the normal scala behaviour which might confuse users. Code snippet from JIRA : ``` val a = spark.createDataset(Map(1->1, 2->2) :: Nil) val b = spark.createDataset(Map(2->2, 1->1) :: Nil) // Demonstration of how Scala Map equality is unaffected by insertion order: assert(Map(1->1, 2->2).hashCode() == Map(2->2, 1->1).hashCode()) assert(Map(1->1, 2->2) == Map(2->2, 1->1)) assert(a.first() == b.first()) // In contrast, this will print two different hashcodes: println(Seq(a, b).map(_.selectExpr("hash(*)").first())) ``` Also `MapType` is prohibited for aggregation / joins / equality comparisons #7819 and set operations #17236. ### Does this PR introduce any user-facing change? Yes. Now users cannot use hash functions on elements of `mapType`. To restore the previous behaviour set `spark.sql.legacy.useHashOnMapType` to true. ### How was this patch tested? UT added. Closes #27580 from iRakson/SPARK-27619. Authored-by: iRakson <raksonrakesh@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request? `hash()` and `xxhash64()` cannot be used on elements of `Maptype`. A new configuration `spark.sql.legacy.useHashOnMapType` is introduced to allow users to restore the previous behaviour. When `spark.sql.legacy.useHashOnMapType` is set to false: ``` scala> spark.sql("select hash(map())"); org.apache.spark.sql.AnalysisException: cannot resolve 'hash(map())' due to data type mismatch: input to function hash cannot contain elements of MapType; line 1 pos 7; 'Project [unresolvedalias(hash(map(), 42), None)] +- OneRowRelation ``` when `spark.sql.legacy.useHashOnMapType` is set to true : ``` scala> spark.sql("set spark.sql.legacy.useHashOnMapType=true"); res3: org.apache.spark.sql.DataFrame = [key: string, value: string] scala> spark.sql("select hash(map())").first() res4: org.apache.spark.sql.Row = [42] ``` ### Why are the changes needed? As discussed in Jira, SparkSql's map hashcodes depends on their order of insertion which is not consistent with the normal scala behaviour which might confuse users. Code snippet from JIRA : ``` val a = spark.createDataset(Map(1->1, 2->2) :: Nil) val b = spark.createDataset(Map(2->2, 1->1) :: Nil) // Demonstration of how Scala Map equality is unaffected by insertion order: assert(Map(1->1, 2->2).hashCode() == Map(2->2, 1->1).hashCode()) assert(Map(1->1, 2->2) == Map(2->2, 1->1)) assert(a.first() == b.first()) // In contrast, this will print two different hashcodes: println(Seq(a, b).map(_.selectExpr("hash(*)").first())) ``` Also `MapType` is prohibited for aggregation / joins / equality comparisons apache#7819 and set operations apache#17236. ### Does this PR introduce any user-facing change? Yes. Now users cannot use hash functions on elements of `mapType`. To restore the previous behaviour set `spark.sql.legacy.useHashOnMapType` to true. ### How was this patch tested? UT added. Closes apache#27580 from iRakson/SPARK-27619. Authored-by: iRakson <raksonrakesh@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> (cherry picked from commit c913b9d) Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request? `hash()` and `xxhash64()` cannot be used on elements of `Maptype`. A new configuration `spark.sql.legacy.useHashOnMapType` is introduced to allow users to restore the previous behaviour. When `spark.sql.legacy.useHashOnMapType` is set to false: ``` scala> spark.sql("select hash(map())"); org.apache.spark.sql.AnalysisException: cannot resolve 'hash(map())' due to data type mismatch: input to function hash cannot contain elements of MapType; line 1 pos 7; 'Project [unresolvedalias(hash(map(), 42), None)] +- OneRowRelation ``` when `spark.sql.legacy.useHashOnMapType` is set to true : ``` scala> spark.sql("set spark.sql.legacy.useHashOnMapType=true"); res3: org.apache.spark.sql.DataFrame = [key: string, value: string] scala> spark.sql("select hash(map())").first() res4: org.apache.spark.sql.Row = [42] ``` ### Why are the changes needed? As discussed in Jira, SparkSql's map hashcodes depends on their order of insertion which is not consistent with the normal scala behaviour which might confuse users. Code snippet from JIRA : ``` val a = spark.createDataset(Map(1->1, 2->2) :: Nil) val b = spark.createDataset(Map(2->2, 1->1) :: Nil) // Demonstration of how Scala Map equality is unaffected by insertion order: assert(Map(1->1, 2->2).hashCode() == Map(2->2, 1->1).hashCode()) assert(Map(1->1, 2->2) == Map(2->2, 1->1)) assert(a.first() == b.first()) // In contrast, this will print two different hashcodes: println(Seq(a, b).map(_.selectExpr("hash(*)").first())) ``` Also `MapType` is prohibited for aggregation / joins / equality comparisons apache#7819 and set operations apache#17236. ### Does this PR introduce any user-facing change? Yes. Now users cannot use hash functions on elements of `mapType`. To restore the previous behaviour set `spark.sql.legacy.useHashOnMapType` to true. ### How was this patch tested? UT added. Closes apache#27580 from iRakson/SPARK-27619. Authored-by: iRakson <raksonrakesh@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
@iRakson @cloud-fan @tarekbecker @w4-sjcho @yhuai @sameeragarwal @hvanhovell |
You can turn map into array by |
What changes were proposed in this pull request?
In spark SQL, map type can't be used in equality test/comparison, and
Intersect
/Except
/Distinct
do need equality test for all columns, we should not allow map type inIntersect
/Except
/Distinct
.How was this patch tested?
new regression test