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sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilterSuite.scala

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@@ -34,6 +34,10 @@ import org.apache.spark.sql.types._
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/**
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* A test suite that tests Apache ORC filter API based filter pushdown optimization.
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* OrcFilterSuite and HiveOrcFilterSuite is logically duplicated to provide the same test coverage.
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* The difference are the packages containing 'Predicate' and 'SearchArgument' classes.
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* - OrcFilterSuite uses 'org.apache.orc.storage.ql.io.sarg' package.
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* - HiveOrcFilterSuite uses 'org.apache.hadoop.hive.ql.io.sarg' package.
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*/
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class OrcFilterSuite extends OrcTest with SharedSQLContext {
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@@ -287,11 +291,6 @@ class OrcFilterSuite extends OrcTest with SharedSQLContext {
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test("filter pushdown - combinations with logical operators") {
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withOrcDataFrame((1 to 4).map(i => Tuple1(Option(i)))) { implicit df =>
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// Because `ExpressionTree` is not accessible at Hive 1.2.x, this should be checked
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// in string form in order to check filter creation including logical operators
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// such as `and`, `or` or `not`. So, this function uses `SearchArgument.toString()`
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// to produce string expression and then compare it to given string expression below.
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// This might have to be changed after Hive version is upgraded.
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checkFilterPredicate(
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'_1.isNotNull,
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"leaf-0 = (IS_NULL _1), expr = (not leaf-0)"

sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcFilterSuite.scala

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@@ -31,7 +31,6 @@ import org.apache.spark.sql.catalyst.planning.PhysicalOperation
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import org.apache.spark.sql.execution.datasources.{DataSourceStrategy, HadoopFsRelation, LogicalRelation}
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import org.apache.spark.sql.execution.datasources.orc.OrcTest
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import org.apache.spark.sql.hive.test.TestHiveSingleton
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import org.apache.spark.sql.internal.SQLConf.ORC_IMPLEMENTATION
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import org.apache.spark.sql.types._
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/**

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