Merge branch 'master' into SPARK-8103

build/mvn

@@ -112,10 +112,17 @@ install_scala() {
 # the environment
 ZINC_PORT=${ZINC_PORT:-"3030"}
 
+# Check for the `--force` flag dictating that `mvn` should be downloaded
+# regardless of whether the system already has a `mvn` install
+if [ "$1" == "--force" ]; then
+  FORCE_MVN=1
+  shift
+fi
+
 # Install Maven if necessary
 MVN_BIN="$(command -v mvn)"
 
-if [ ! "$MVN_BIN" ]; then
+if [ ! "$MVN_BIN" -o -n "$FORCE_MVN" ]; then
   install_mvn
 fi
 
@@ -139,5 +146,7 @@ fi
 # Set any `mvn` options if not already present
 export MAVEN_OPTS=${MAVEN_OPTS:-"$_COMPILE_JVM_OPTS"}
 
+echo "Using \`mvn\` from path: $MVN_BIN"
+
 # Last, call the `mvn` command as usual
 ${MVN_BIN} "$@"

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionals.scala

@@ -230,24 +230,31 @@ case class CaseKeyWhen(key: Expression, branches: Seq[Expression]) extends CaseW
     }
   }
 
+  private def evalElse(input: InternalRow): Any = {
+    if (branchesArr.length % 2 == 0) {
+      null
+    } else {
+      branchesArr(branchesArr.length - 1).eval(input)
+    }
+  }
+
   /** Written in imperative fashion for performance considerations. */
   override def eval(input: InternalRow): Any = {
     val evaluatedKey = key.eval(input)
-    val len = branchesArr.length
-    var i = 0
-    // If all branches fail and an elseVal is not provided, the whole statement
-    // defaults to null, according to Hive's semantics.
-    while (i < len - 1) {
-      if (threeValueEquals(evaluatedKey, branchesArr(i).eval(input))) {
-        return branchesArr(i + 1).eval(input)
+    // If key is null, we can just return the else part or null if there is no else.
+    // If key is not null but doesn't match any when part, we need to return
+    // the else part or null if there is no else, according to Hive's semantics.
+    if (evaluatedKey != null) {
+      val len = branchesArr.length
+      var i = 0
+      while (i < len - 1) {
+        if (evaluatedKey ==  branchesArr(i).eval(input)) {
+          return branchesArr(i + 1).eval(input)
+        }
+        i += 2
       }
-      i += 2
     }
-    var res: Any = null
-    if (i == len - 1) {
-      res = branchesArr(i).eval(input)
-    }
-    return res
+    evalElse(input)
   }
 
   override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = {
@@ -261,8 +268,7 @@ case class CaseKeyWhen(key: Expression, branches: Seq[Expression]) extends CaseW
       s"""
         if (!$got) {
           ${cond.code}
-          if (!${keyEval.isNull} && !${cond.isNull}
-             && ${ctx.genEqual(key.dataType, keyEval.primitive, cond.primitive)}) {
+          if (!${cond.isNull} && ${ctx.genEqual(key.dataType, keyEval.primitive, cond.primitive)}) {
             $got = true;
             ${res.code}
             ${ev.isNull} = ${res.isNull};
@@ -290,19 +296,13 @@ case class CaseKeyWhen(key: Expression, branches: Seq[Expression]) extends CaseW
       boolean ${ev.isNull} = true;
       ${ctx.javaType(dataType)} ${ev.primitive} = ${ctx.defaultValue(dataType)};
       ${keyEval.code}
-      $cases
+      if (!${keyEval.isNull}) {
+        $cases
+      }
       $other
     """
   }
 
-  private def threeValueEquals(l: Any, r: Any) = {
-    if (l == null || r == null) {
-      false
-    } else {
-      l == r
-    }
-  }
-
   override def toString: String = {
     s"CASE $key" + branches.sliding(2, 2).map {
       case Seq(cond, value) => s" WHEN $cond THEN $value"

sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveShim.scala

@@ -34,7 +34,7 @@ import org.apache.hadoop.hive.ql.session.SessionState
 import org.apache.hadoop.hive.serde.serdeConstants
 
 import org.apache.spark.Logging
-import org.apache.spark.sql.catalyst.expressions.{Expression, AttributeReference, BinaryComparison}
+import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.types.{StringType, IntegralType}
 
 /**
@@ -312,37 +312,41 @@ private[client] class Shim_v0_13 extends Shim_v0_12 {
   override def getAllPartitions(hive: Hive, table: Table): Seq[Partition] =
     getAllPartitionsMethod.invoke(hive, table).asInstanceOf[JSet[Partition]].toSeq
 
-  override def getPartitionsByFilter(
-      hive: Hive,
-      table: Table,
-      predicates: Seq[Expression]): Seq[Partition] = {
+  /**
+   * Converts catalyst expression to the format that Hive's getPartitionsByFilter() expects, i.e.
+   * a string that represents partition predicates like "str_key=\"value\" and int_key=1 ...".
+   *
+   * Unsupported predicates are skipped.
+   */
+  def convertFilters(table: Table, filters: Seq[Expression]): String = {
     // hive varchar is treated as catalyst string, but hive varchar can't be pushed down.
     val varcharKeys = table.getPartitionKeys
       .filter(col => col.getType.startsWith(serdeConstants.VARCHAR_TYPE_NAME))
       .map(col => col.getName).toSet
 
-    // Hive getPartitionsByFilter() takes a string that represents partition
-    // predicates like "str_key=\"value\" and int_key=1 ..."
-    val filter = predicates.flatMap { expr =>
-      expr match {
-        case op @ BinaryComparison(lhs, rhs) => {
-          lhs match {
-            case AttributeReference(_, _, _, _) => {
-              rhs.dataType match {
-                case _: IntegralType =>
-                  Some(lhs.prettyString + op.symbol + rhs.prettyString)
-                case _: StringType if (!varcharKeys.contains(lhs.prettyString)) =>
-                  Some(lhs.prettyString + op.symbol + "\"" + rhs.prettyString + "\"")
-                case _ => None
-              }
-            }
-            case _ => None
-          }
-        }
-        case _ => None
-      }
+    filters.collect {
+      case op @ BinaryComparison(a: Attribute, Literal(v, _: IntegralType)) =>
+        s"${a.name} ${op.symbol} $v"
+      case op @ BinaryComparison(Literal(v, _: IntegralType), a: Attribute) =>
+        s"$v ${op.symbol} ${a.name}"
+
+      case op @ BinaryComparison(a: Attribute, Literal(v, _: StringType))
+          if !varcharKeys.contains(a.name) =>
+        s"""${a.name} ${op.symbol} "$v""""
+      case op @ BinaryComparison(Literal(v, _: StringType), a: Attribute)
+          if !varcharKeys.contains(a.name) =>
+        s""""$v" ${op.symbol} ${a.name}"""
     }.mkString(" and ")
+  }
+
+  override def getPartitionsByFilter(
+      hive: Hive,
+      table: Table,
+      predicates: Seq[Expression]): Seq[Partition] = {
 
+    // Hive getPartitionsByFilter() takes a string that represents partition
+    // predicates like "str_key=\"value\" and int_key=1 ..."
+    val filter = convertFilters(table, predicates)
     val partitions =
       if (filter.isEmpty) {
         getAllPartitionsMethod.invoke(hive, table).asInstanceOf[JSet[Partition]]

sql/hive/src/test/scala/org/apache/spark/sql/hive/client/FiltersSuite.scala

@@ -0,0 +1,78 @@
+/*
+ * 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.hive.client
+
+import scala.collection.JavaConversions._
+
+import org.apache.hadoop.hive.metastore.api.FieldSchema
+import org.apache.hadoop.hive.serde.serdeConstants
+
+import org.apache.spark.{Logging, SparkFunSuite}
+import org.apache.spark.sql.catalyst.dsl.expressions._
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.types._
+
+/**
+ * A set of tests for the filter conversion logic used when pushing partition pruning into the
+ * metastore
+ */
+class FiltersSuite extends SparkFunSuite with Logging {
+  private val shim = new Shim_v0_13
+
+  private val testTable = new org.apache.hadoop.hive.ql.metadata.Table("default", "test")
+  private val varCharCol = new FieldSchema()
+  varCharCol.setName("varchar")
+  varCharCol.setType(serdeConstants.VARCHAR_TYPE_NAME)
+  testTable.setPartCols(varCharCol :: Nil)
+
+  filterTest("string filter",
+    (a("stringcol", StringType) > Literal("test")) :: Nil,
+    "stringcol > \"test\"")
+
+  filterTest("string filter backwards",
+    (Literal("test") > a("stringcol", StringType)) :: Nil,
+    "\"test\" > stringcol")
+
+  filterTest("int filter",
+    (a("intcol", IntegerType) === Literal(1)) :: Nil,
+    "intcol = 1")
+
+  filterTest("int filter backwards",
+    (Literal(1) === a("intcol", IntegerType)) :: Nil,
+    "1 = intcol")
+
+  filterTest("int and string filter",
+    (Literal(1) === a("intcol", IntegerType)) :: (Literal("a") === a("strcol", IntegerType)) :: Nil,
+    "1 = intcol and \"a\" = strcol")
+
+  filterTest("skip varchar",
+    (Literal("") === a("varchar", StringType)) :: Nil,
+    "")
+
+  private def filterTest(name: String, filters: Seq[Expression], result: String) = {
+    test(name){
+      val converted = shim.convertFilters(testTable, filters)
+      if (converted != result) {
+        fail(
+          s"Expected filters ${filters.mkString(",")} to convert to '$result' but got '$converted'")
+      }
+    }
+  }
+
+  private def a(name: String, dataType: DataType) = AttributeReference(name, dataType)()
+}