[SPARK-47483][SQL] Add support for aggregation and join operations on arrays of collated strings #45611
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| Original file line number | Diff line number | Diff line change |
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@@ -27,10 +27,11 @@ import org.apache.spark.sql.connector.{DatasourceV2SQLBase, FakeV2ProviderWithCu | |
| import org.apache.spark.sql.connector.catalog.{Identifier, InMemoryTable} | ||
| import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.CatalogHelper | ||
| import org.apache.spark.sql.connector.catalog.CatalogV2Util.withDefaultOwnership | ||
| import org.apache.spark.sql.errors.DataTypeErrors.toSQLType | ||
| import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper | ||
| import org.apache.spark.sql.execution.aggregate.{HashAggregateExec, ObjectHashAggregateExec} | ||
| import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, SortMergeJoinExec} | ||
| import org.apache.spark.sql.types.{MapType, StringType, StructField, StructType} | ||
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| class CollationSuite extends DatasourceV2SQLBase with AdaptiveSparkPlanHelper { | ||
| protected val v2Source = classOf[FakeV2ProviderWithCustomSchema].getName | ||
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@@ -640,6 +641,90 @@ class CollationSuite extends DatasourceV2SQLBase with AdaptiveSparkPlanHelper { | |
| "reason" -> "generation expression cannot contain non-default collated string type")) | ||
| } | ||
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| test("Aggregation on complex containing collated strings") { | ||
| val table = "table_agg" | ||
| // array | ||
| withTable(table) { | ||
| sql(s"create table $table (a array<string collate utf8_binary_lcase>) using parquet") | ||
| sql(s"insert into $table values (array('aaa')), (array('AAA'))") | ||
| checkAnswer(sql(s"select distinct a from $table"), Seq(Row(Seq("aaa")))) | ||
| } | ||
| // map doesn't support aggregation | ||
| withTable(table) { | ||
| sql(s"create table $table (m map<string collate utf8_binary_lcase, string>) using parquet") | ||
| val query = s"select distinct m from $table" | ||
| checkError( | ||
| exception = intercept[ExtendedAnalysisException](sql(query)), | ||
| errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE", | ||
| parameters = Map( | ||
| "colName" -> "`m`", | ||
| "dataType" -> toSQLType(MapType( | ||
| StringType(CollationFactory.collationNameToId("UTF8_BINARY_LCASE")), | ||
| StringType))), | ||
| context = ExpectedContext(query, 0, query.length - 1) | ||
| ) | ||
| } | ||
| // struct | ||
| withTable(table) { | ||
| sql(s"create table $table (s struct<fld:string collate utf8_binary_lcase>) using parquet") | ||
| sql(s"insert into $table values (named_struct('fld', 'aaa')), (named_struct('fld', 'AAA'))") | ||
| checkAnswer(sql(s"select s.fld from $table group by s"), Seq(Row("aaa"))) | ||
| } | ||
| } | ||
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| test("Joins on complex types containing collated strings") { | ||
| val tableLeft = "table_join_le" | ||
| val tableRight = "table_join_ri" | ||
| // array | ||
| withTable(tableLeft, tableRight) { | ||
| Seq(tableLeft, tableRight).map(tab => | ||
| sql(s"create table $tab (a array<string collate utf8_binary_lcase>) using parquet")) | ||
| Seq((tableLeft, "array('aaa')"), (tableRight, "array('AAA')")).map{ | ||
| case (tab, data) => sql(s"insert into $tab values ($data)") | ||
| } | ||
| checkAnswer(sql( | ||
| s""" | ||
| |select $tableLeft.a from $tableLeft | ||
| |join $tableRight on $tableLeft.a = $tableRight.a | ||
| |""".stripMargin), Seq(Row(Seq("aaa")))) | ||
| } | ||
| // map doesn't support joins | ||
| withTable(tableLeft, tableRight) { | ||
| Seq(tableLeft, tableRight).map(tab => | ||
| sql(s"create table $tab (m map<string collate utf8_binary_lcase, string>) using parquet")) | ||
| val query = | ||
| s"select $tableLeft.m from $tableLeft join $tableRight on $tableLeft.m = $tableRight.m" | ||
| val ctx = s"$tableLeft.m = $tableRight.m" | ||
| checkError( | ||
| exception = intercept[AnalysisException](sql(query)), | ||
| errorClass = "DATATYPE_MISMATCH.INVALID_ORDERING_TYPE", | ||
| parameters = Map( | ||
| "functionName" -> "`=`", | ||
| "dataType" -> toSQLType(MapType( | ||
| StringType(CollationFactory.collationNameToId("UTF8_BINARY_LCASE")), | ||
| StringType | ||
| )), | ||
| "sqlExpr" -> "\"(m = m)\""), | ||
| context = ExpectedContext(ctx, query.length - ctx.length, query.length - 1)) | ||
| } | ||
| // struct | ||
| withTable(tableLeft, tableRight) { | ||
| Seq(tableLeft, tableRight).map(tab => | ||
| sql(s"create table $tab (s struct<fld:string collate utf8_binary_lcase>) using parquet")) | ||
| Seq( | ||
| (tableLeft, "named_struct('fld', 'aaa')"), | ||
| (tableRight, "named_struct('fld', 'AAA')") | ||
| ).map { | ||
| case (tab, data) => sql(s"insert into $tab values ($data)") | ||
| } | ||
| checkAnswer(sql( | ||
| s""" | ||
| |select $tableLeft.s.fld from $tableLeft | ||
| |join $tableRight on $tableLeft.s = $tableRight.s | ||
| |""".stripMargin), Seq(Row("aaa"))) | ||
| } | ||
| } | ||
|
There was a problem hiding this comment. The test pattern that can be useful here is what we did for Window Aggs. You can find test example here: There was a problem hiding this comment. Updated tests to support this and added case classes for better readability. Please check again. |
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| test("window aggregates should respect collation") { | ||
| val t1 = "T_NON_BINARY" | ||
| val t2 = "T_BINARY" | ||
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why
isBinaryStableis inUnsafeRowUtils. Is the implementation bound somehow to unsafe row?Why it is not in
DataTypeUtilsorCollation..., for example?There was a problem hiding this comment.
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Not sure what are the consequences of moving this function, do you know if we can do that @dbatomic?