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zxmRrWU}3XWE}BQ=`QJqqc#Arft}{8ix{9!IEUER+G%6M(5MHv9tzhozC;QR}oqx_GE;CmHC+YzT1~`IVECF$h?M2m&Ds9yJV@dBJ(G*2Z4-6Z2NwwD`{qDGrG?ZOiyD_{U0#oUoj6eJS6C&R$o4OaR9 literal 0 HcmV?d00001 diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala index 36c764efaedfc..0b7e8b46e4489 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala @@ -297,20 +297,22 @@ class ApproximatePercentileQuerySuite extends QueryTest with SharedSparkSession assert(buffer.isCompressed) } - test("SPARK-XXXXX: ") { + test("SPARK-32908: maximum target error in percentile_approx") { withTempView(table) { - val df = spark.read.option("header", "true") - .option("inferSchema", "true") - .csv("/Users/maximgekk/tmp/tr_rat_resampling_score.csv") + spark.read + .schema("col int") + .csv(testFile("percentile_approx-input.csv.bz2")) .repartition(1) - df.createOrReplaceTempView(table) + .createOrReplaceTempView(table) checkAnswer( spark.sql( s"""SELECT - | percentile_approx(tr_rat_resampling_score, 0.77, 100000) - |FROM $table - """.stripMargin), - Row(17)) + | percentile_approx(col, 0.77, 1000), + | percentile_approx(col, 0.77, 10000), + | percentile_approx(col, 0.77, 100000), + | percentile_approx(col, 0.77, 1000000) + |FROM $table""".stripMargin), + Row(18, 17, 17, 17)) } } }