[SPARK-18413][SQL][FOLLOW-UP] Use numPartitions instead of maxConnections

docs/sql-programming-guide.md

@@ -1061,17 +1061,28 @@ the following case-sensitive options:
   </tr>
 
   <tr>
-    <td><code>partitionColumn, lowerBound, upperBound, numPartitions</code></td>
+    <td><code>partitionColumn, lowerBound, upperBound</code></td>
     <td>
-      These options must all be specified if any of them is specified. They describe how to
-      partition the table when reading in parallel from multiple workers.
+      These options must all be specified if any of them is specified. In addition,
+      <code>numPartitions</code> must be specified. They describe how to partition the table when
+      reading in parallel from multiple workers.
       <code>partitionColumn</code> must be a numeric column from the table in question. Notice
       that <code>lowerBound</code> and <code>upperBound</code> are just used to decide the
       partition stride, not for filtering the rows in table. So all rows in the table will be
       partitioned and returned. This option applies only to reading.
     </td>
   </tr>
 
+  <tr>
+     <td><code>numPartitions</code></td>
+     <td>
+       The maximum number of partitions that can be used for parallelism in table reading and
+       writing. This also determines the maximum number of concurrent JDBC connections.
+       If the number of partitions to write exceeds this limit, we decrease it to this limit by
+       calling <code>coalesce(numPartitions)</code> before writing.
+     </td>
+  </tr>
+
   <tr>
     <td><code>fetchsize</code></td>
     <td>
@@ -1086,13 +1097,6 @@ the following case-sensitive options:
      </td>
   </tr>
 
-  <tr>
-     <td><code>maxConnections</code></td>
-     <td>
-       The maximum number of concurrent JDBC connections that can be used, if set. Only applies when writing. It works by limiting the operation's parallelism, which depends on the input's partition count. If its partition count exceeds this limit, the operation will coalesce the input to fewer partitions before writing.
-     </td>
-  </tr>
-
   <tr>
      <td><code>isolationLevel</code></td>
      <td>

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala

@@ -74,19 +74,23 @@ class JDBCOptions(
     }
   }
 
+  // the number of partitions
+  val numPartitions = parameters.get(JDBC_NUM_PARTITIONS).map(_.toInt)
+  require(numPartitions.isEmpty || numPartitions.get > 0,
+    s"Invalid value `${numPartitions.get}` for parameter `$JDBC_NUM_PARTITIONS`. " +
+      "The minimum value is 1.")
+
   // ------------------------------------------------------------
   // Optional parameters only for reading
   // ------------------------------------------------------------
   // the column used to partition
-  val partitionColumn = parameters.getOrElse(JDBC_PARTITION_COLUMN, null)
+  val partitionColumn = parameters.get(JDBC_PARTITION_COLUMN)
   // the lower bound of partition column
-  val lowerBound = parameters.getOrElse(JDBC_LOWER_BOUND, null)
+  val lowerBound = parameters.get(JDBC_LOWER_BOUND).map(_.toLong)
   // the upper bound of the partition column
-  val upperBound = parameters.getOrElse(JDBC_UPPER_BOUND, null)
-  // the number of partitions
-  val numPartitions = parameters.getOrElse(JDBC_NUM_PARTITIONS, null)
-  require(partitionColumn == null ||
-    (lowerBound != null && upperBound != null && numPartitions != null),
+  val upperBound = parameters.get(JDBC_UPPER_BOUND).map(_.toLong)
+  require(partitionColumn.isEmpty ||
+    (lowerBound.isDefined && upperBound.isDefined && numPartitions.isDefined),
     s"If '$JDBC_PARTITION_COLUMN' is specified then '$JDBC_LOWER_BOUND', '$JDBC_UPPER_BOUND'," +
       s" and '$JDBC_NUM_PARTITIONS' are required.")
   val fetchSize = {
@@ -122,11 +126,6 @@ class JDBCOptions(
       case "REPEATABLE_READ" => Connection.TRANSACTION_REPEATABLE_READ
       case "SERIALIZABLE" => Connection.TRANSACTION_SERIALIZABLE
     }
-  // the maximum number of connections
-  val maxConnections = parameters.get(JDBC_MAX_CONNECTIONS).map(_.toInt)
-  require(maxConnections.isEmpty || maxConnections.get > 0,
-    s"Invalid value `${maxConnections.get}` for parameter `$JDBC_MAX_CONNECTIONS`. " +
-      "The minimum value is 1.")
 }
 
 object JDBCOptions {
@@ -149,5 +148,4 @@ object JDBCOptions {
   val JDBC_CREATE_TABLE_OPTIONS = newOption("createTableOptions")
   val JDBC_BATCH_INSERT_SIZE = newOption("batchsize")
   val JDBC_TXN_ISOLATION_LEVEL = newOption("isolationLevel")
-  val JDBC_MAX_CONNECTIONS = newOption("maxConnections")
 }

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcRelationProvider.scala

@@ -35,11 +35,13 @@ class JdbcRelationProvider extends CreatableRelationProvider
     val upperBound = jdbcOptions.upperBound
     val numPartitions = jdbcOptions.numPartitions
 
-    val partitionInfo = if (partitionColumn == null) {
+    val partitionInfo = if (partitionColumn.isEmpty) {
+      assert(lowerBound.isEmpty && upperBound.isEmpty)
       null
     } else {
+      assert(lowerBound.nonEmpty && upperBound.nonEmpty && numPartitions.nonEmpty)
       JDBCPartitioningInfo(
-        partitionColumn, lowerBound.toLong, upperBound.toLong, numPartitions.toInt)
+        partitionColumn.get, lowerBound.get, upperBound.get, numPartitions.get)
     }
     val parts = JDBCRelation.columnPartition(partitionInfo)
     JDBCRelation(parts, jdbcOptions)(sqlContext.sparkSession)

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala

@@ -667,10 +667,10 @@ object JdbcUtils extends Logging {
     val getConnection: () => Connection = createConnectionFactory(options)
     val batchSize = options.batchSize
     val isolationLevel = options.isolationLevel
-    val maxConnections = options.maxConnections
+    val numPartitions = options.numPartitions
     val repartitionedDF =
-      if (maxConnections.isDefined && maxConnections.get < df.rdd.getNumPartitions) {
-        df.coalesce(maxConnections.get)
+      if (numPartitions.isDefined && numPartitions.get < df.rdd.getNumPartitions) {
+        df.coalesce(numPartitions.get)
       } else {
         df
       }

sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala

@@ -313,15 +313,15 @@ class JDBCWriteSuite extends SharedSQLContext with BeforeAndAfter {
       .save()
   }
 
-  test("SPARK-18413: Add `maxConnections` JDBCOption") {
+  test("SPARK-18413: Use `numPartitions` JDBCOption") {
     val df = spark.createDataFrame(sparkContext.parallelize(arr2x2), schema2)
     val e = intercept[IllegalArgumentException] {
       df.write.format("jdbc")
         .option("dbtable", "TEST.SAVETEST")
         .option("url", url1)
-        .option(s"${JDBCOptions.JDBC_MAX_CONNECTIONS}", "0")
+        .option(s"${JDBCOptions.JDBC_NUM_PARTITIONS}", "0")
         .save()
     }.getMessage
-    assert(e.contains("Invalid value `0` for parameter `maxConnections`. The minimum value is 1"))
+    assert(e.contains("Invalid value `0` for parameter `numPartitions`. The minimum value is 1"))
   }
 }