wangyum commented on a change in pull request #35789: URL: https://github.com/apache/spark/pull/35789#discussion_r824385275
########## File path: sql/core/src/test/scala/org/apache/spark/sql/BloomFilterAggregateQuerySuite.scala ########## @@ -0,0 +1,202 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.apache.spark.sql.catalyst.FunctionIdentifier +import org.apache.spark.sql.catalyst.analysis.FunctionRegistry +import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.catalyst.expressions.aggregate.BloomFilterAggregate +import org.apache.spark.sql.execution.aggregate.BaseAggregateExec +import org.apache.spark.sql.test.SharedSparkSession + +/** + * Query tests for the Bloom filter aggregate and filter function. + */ +class BloomFilterAggregateQuerySuite extends QueryTest with SharedSparkSession { + import testImplicits._ + + // Register 'bloom_filter_agg' to builtin. + FunctionRegistry.builtin.registerFunction(new FunctionIdentifier("bloom_filter_agg"), + new ExpressionInfo(classOf[BloomFilterAggregate].getName, "bloom_filter_agg"), + (children: Seq[Expression]) => children.size match { + case 1 => new BloomFilterAggregate(children.head) + case 2 => new BloomFilterAggregate(children.head, children(1)) + case 3 => new BloomFilterAggregate(children.head, children(1), children(2)) + }) + + // Register 'might_contain' to builtin. + FunctionRegistry.builtin.registerFunction(new FunctionIdentifier("might_contain"), + new ExpressionInfo(classOf[BloomFilterMightContain].getName, "might_contain"), + (children: Seq[Expression]) => BloomFilterMightContain(children.head, children(1))) + + test("Test bloom_filter_agg and might_contain") { + val table = "bloom_filter_test" + for (numEstimatedItems <- Seq(Long.MinValue, -10L, 0L, 4096L, 4194304L, Long.MaxValue, + BloomFilterAggregate.MAX_ALLOWED_NUM_ITEMS)) { + for (numBits <- Seq(Long.MinValue, -10L, 0L, 4096L, 4194304L, Long.MaxValue, + BloomFilterAggregate.MAX_NUM_BITS)) { + val sqlString = s""" + |SELECT every(might_contain( + | (SELECT bloom_filter_agg(col, + | cast($numEstimatedItems as long), + | cast($numBits as long)) + | FROM $table), + | col)) positive_membership_test, + | every(might_contain( + | (SELECT bloom_filter_agg(col, + | cast($numEstimatedItems as long), + | cast($numBits as long)) + | FROM values (-1L), (100001L), (20000L) as t(col)), + | col)) negative_membership_test + |FROM $table + """.stripMargin + withTempView(table) { + (Seq(Long.MinValue, 0, Long.MaxValue) ++ (1L to 10000L)) + .toDF("col").createOrReplaceTempView(table) + // Validate error messages as well as answers when there's no error. + if (numEstimatedItems <= 0) { + val exception = intercept[AnalysisException] { + spark.sql(sqlString) + } + assert(exception.getMessage.contains( + "The estimated number of items must be a positive value")) + } else if (numBits <= 0) { + val exception = intercept[AnalysisException] { + spark.sql(sqlString) + } + assert(exception.getMessage.contains("The number of bits must be a positive value")) + } else { + checkAnswer(spark.sql(sqlString), Row(true, false)) + } + } + } + } + } + + test("Test that bloom_filter_agg errors out disallowed input value types") { + val exception1 = intercept[AnalysisException] { + spark.sql(""" + |SELECT bloom_filter_agg(a) + |FROM values (1.2), (2.5) as t(a)""" + .stripMargin) + } + assert(exception1.getMessage.contains( + "Input to function bloom_filter_agg should have been a bigint value")) + + val exception2 = intercept[AnalysisException] { + spark.sql(""" + |SELECT bloom_filter_agg(a, 2) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception2.getMessage.contains( + "function bloom_filter_agg should have been a bigint value followed with two bigint")) + + val exception3 = intercept[AnalysisException] { + spark.sql(""" + |SELECT bloom_filter_agg(a, cast(2 as long), 5) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception3.getMessage.contains( + "function bloom_filter_agg should have been a bigint value followed with two bigint")) + + val exception4 = intercept[AnalysisException] { + spark.sql(""" + |SELECT bloom_filter_agg(a, null, 5) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception4.getMessage.contains("Null typed values cannot be used as size arguments")) + + val exception5 = intercept[AnalysisException] { + spark.sql(""" + |SELECT bloom_filter_agg(a, 5, null) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception5.getMessage.contains("Null typed values cannot be used as size arguments")) + } + + test("Test that might_contain errors out disallowed input value types") { + val exception1 = intercept[AnalysisException] { + spark.sql("""|SELECT might_contain(1.0, 1L)""" + .stripMargin) + } + assert(exception1.getMessage.contains( + "Input to function might_contain should have been binary followed by a value with bigint")) + + val exception2 = intercept[AnalysisException] { + spark.sql("""|SELECT might_contain(NULL, 0.1)""" + .stripMargin) + } + assert(exception2.getMessage.contains( + "Input to function might_contain should have been binary followed by a value with bigint")) + } + + test("Test that might_contain errors out non-constant Bloom filter") { + val exception1 = intercept[AnalysisException] { + spark.sql(""" + |SELECT might_contain(cast(a as binary), cast(5 as long)) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception1.getMessage.contains( + "The Bloom filter binary input to might_contain should be either a constant value or " + + "a scalar subquery expression")) + + val exception2 = intercept[AnalysisException] { + spark.sql(""" + |SELECT might_contain((select cast(a as binary)), cast(5 as long)) + |FROM values (cast(1 as long)), (cast(2 as long)) as t(a)""" + .stripMargin) + } + assert(exception2.getMessage.contains( + "The Bloom filter binary input to might_contain should be either a constant value or " + + "a scalar subquery expression")) + } + + test("Test that might_contain can take a constant value input") { + checkAnswer(spark.sql( + """SELECT might_contain( + |X'00000001000000050000000343A2EC6EA8C117E2D3CDB767296B144FC5BFBCED9737F267', + |cast(201 as long))""".stripMargin), + Row(false)) + } + + test("Test that bloom_filter_agg produces a NULL with empty input") { + checkAnswer(spark.sql("""SELECT bloom_filter_agg(cast(id as long)) from range(1, 1)"""), + Row(null)) + } + + test("Test NULL inputs for might_contain") { + checkAnswer(spark.sql( + s""" + |SELECT might_contain(null, null) both_null, + | might_contain(null, 1L) null_bf, + | might_contain((SELECT bloom_filter_agg(cast(id as long)) from range(1, 10000)), + | null) null_value + """.stripMargin), + Row(null, null, null)) + } + + test("Test that a query with bloom_filter_agg has partial aggregates") { + spark.sql("""SELECT bloom_filter_agg(cast(id as long)) from range(1, 1000000)""") + .queryExecution.executedPlan.collect({case agg: BaseAggregateExec => agg}).size == 2 Review comment: Missing assert? -- This is an automated message from the Apache Git Service. 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