diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
index 1af2f9afea5eb421498a992925e51d8fb8d22b7c..365b50dee93c4d89e1d07c99e23dc4258c30daf0 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
@@ -159,7 +159,11 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
* @since 1.4.0
*/
def jdbc(url: String, table: String, properties: Properties): DataFrame = {
- jdbc(url, table, JDBCRelation.columnPartition(null), properties)
+ // properties should override settings in extraOptions.
+ this.extraOptions = this.extraOptions ++ properties.asScala
+ // explicit url and dbtable should override all
+ this.extraOptions += (JDBCOptions.JDBC_URL -> url, JDBCOptions.JDBC_TABLE_NAME -> table)
+ format("jdbc").load()
}
/**
@@ -177,7 +181,8 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
* @param upperBound the maximum value of `columnName` used to decide partition stride.
* @param numPartitions the number of partitions. This, along with `lowerBound` (inclusive),
* `upperBound` (exclusive), form partition strides for generated WHERE
- * clause expressions used to split the column `columnName` evenly.
+ * clause expressions used to split the column `columnName` evenly. When
+ * the input is less than 1, the number is set to 1.
* @param connectionProperties JDBC database connection arguments, a list of arbitrary string
* tag/value. Normally at least a "user" and "password" property
* should be included. "fetchsize" can be used to control the
@@ -192,9 +197,13 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
upperBound: Long,
numPartitions: Int,
connectionProperties: Properties): DataFrame = {
- val partitioning = JDBCPartitioningInfo(columnName, lowerBound, upperBound, numPartitions)
- val parts = JDBCRelation.columnPartition(partitioning)
- jdbc(url, table, parts, connectionProperties)
+ // columnName, lowerBound, upperBound and numPartitions override settings in extraOptions.
+ this.extraOptions ++= Map(
+ JDBCOptions.JDBC_PARTITION_COLUMN -> columnName,
+ JDBCOptions.JDBC_LOWER_BOUND -> lowerBound.toString,
+ JDBCOptions.JDBC_UPPER_BOUND -> upperBound.toString,
+ JDBCOptions.JDBC_NUM_PARTITIONS -> numPartitions.toString)
+ jdbc(url, table, connectionProperties)
}
/**
@@ -220,22 +229,14 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
table: String,
predicates: Array[String],
connectionProperties: Properties): DataFrame = {
+ // connectionProperties should override settings in extraOptions.
+ val params = extraOptions.toMap ++ connectionProperties.asScala.toMap
+ val options = new JDBCOptions(url, table, params)
val parts: Array[Partition] = predicates.zipWithIndex.map { case (part, i) =>
JDBCPartition(part, i) : Partition
}
- jdbc(url, table, parts, connectionProperties)
- }
-
- private def jdbc(
- url: String,
- table: String,
- parts: Array[Partition],
- connectionProperties: Properties): DataFrame = {
- // connectionProperties should override settings in extraOptions.
- this.extraOptions = this.extraOptions ++ connectionProperties.asScala
- // explicit url and dbtable should override all
- this.extraOptions += ("url" -> url, "dbtable" -> table)
- format("jdbc").load()
+ val relation = JDBCRelation(parts, options)(sparkSession)
+ sparkSession.baseRelationToDataFrame(relation)
}
/**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala
index fe2f4c1d78647933008379497620820165a90baf..56cd17816f7bd6ae86ab590a1e9e3eaba605ca0c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala
@@ -76,9 +76,6 @@ 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
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRelation.scala
index 672c21c6ac73458174d1349eb59a0a3a8b24ec63..30caa73adc1eae6914157d1f52d3e886c8c33db7 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRelation.scala
@@ -137,7 +137,8 @@ private[sql] case class JDBCRelation(
}
override def toString: String = {
+ val partitioningInfo = if (parts.nonEmpty) s" [numPartitions=${parts.length}]" else ""
// credentials should not be included in the plan output, table information is sufficient.
- s"JDBCRelation(${jdbcOptions.table})"
+ s"JDBCRelation(${jdbcOptions.table})" + partitioningInfo
}
}
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
index c2a1ad84b952e5378cf977a9b6985c29b55d162a..ff29a15960c5702965e7b13d2392884135fcc840 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
@@ -657,7 +657,7 @@ object JdbcUtils extends Logging {
df: DataFrame,
url: String,
table: String,
- options: JDBCOptions) {
+ options: JDBCOptions): Unit = {
val dialect = JdbcDialects.get(url)
val nullTypes: Array[Int] = df.schema.fields.map { field =>
getJdbcType(field.dataType, dialect).jdbcNullType
@@ -667,13 +667,13 @@ object JdbcUtils extends Logging {
val getConnection: () => Connection = createConnectionFactory(options)
val batchSize = options.batchSize
val isolationLevel = options.isolationLevel
- val numPartitions = options.numPartitions
- val repartitionedDF =
- if (numPartitions.isDefined && numPartitions.get < df.rdd.getNumPartitions) {
- df.coalesce(numPartitions.get)
- } else {
- df
- }
+ val repartitionedDF = options.numPartitions match {
+ case Some(n) if n <= 0 => throw new IllegalArgumentException(
+ s"Invalid value `$n` for parameter `${JDBCOptions.JDBC_NUM_PARTITIONS}` in table writing " +
+ "via JDBC. The minimum value is 1.")
+ case Some(n) if n < df.rdd.getNumPartitions => df.coalesce(n)
+ case _ => df
+ }
repartitionedDF.foreachPartition(iterator => savePartition(
getConnection, table, iterator, rddSchema, nullTypes, batchSize, dialect, isolationLevel)
)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
index b16be457ed5c3bd3e78bd41f501f3765d8bf2e4f..218ccf9332cd67f12490677342583bda6f397716 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
@@ -24,12 +24,12 @@ import java.util.{Calendar, GregorianCalendar, Properties}
import org.h2.jdbc.JdbcSQLException
import org.scalatest.{BeforeAndAfter, PrivateMethodTester}
-import org.apache.spark.{SparkException, SparkFunSuite}
+import org.apache.spark.SparkFunSuite
import org.apache.spark.sql.{DataFrame, Row}
import org.apache.spark.sql.execution.DataSourceScanExec
import org.apache.spark.sql.execution.command.ExplainCommand
import org.apache.spark.sql.execution.datasources.LogicalRelation
-import org.apache.spark.sql.execution.datasources.jdbc.{JDBCOptions, JDBCRDD, JdbcUtils}
+import org.apache.spark.sql.execution.datasources.jdbc.{JDBCOptions, JDBCRDD, JDBCRelation, JdbcUtils}
import org.apache.spark.sql.sources._
import org.apache.spark.sql.test.SharedSQLContext
import org.apache.spark.sql.types._
@@ -209,6 +209,16 @@ class JDBCSuite extends SparkFunSuite
conn.close()
}
+ // Check whether the tables are fetched in the expected degree of parallelism
+ def checkNumPartitions(df: DataFrame, expectedNumPartitions: Int): Unit = {
+ val jdbcRelations = df.queryExecution.analyzed.collect {
+ case LogicalRelation(r: JDBCRelation, _, _) => r
+ }
+ assert(jdbcRelations.length == 1)
+ assert(jdbcRelations.head.parts.length == expectedNumPartitions,
+ s"Expecting a JDBCRelation with $expectedNumPartitions partitions, but got:`$jdbcRelations`")
+ }
+
test("SELECT *") {
assert(sql("SELECT * FROM foobar").collect().size === 3)
}
@@ -313,13 +323,23 @@ class JDBCSuite extends SparkFunSuite
}
test("SELECT * partitioned") {
- assert(sql("SELECT * FROM parts").collect().size == 3)
+ val df = sql("SELECT * FROM parts")
+ checkNumPartitions(df, expectedNumPartitions = 3)
+ assert(df.collect().length == 3)
}
test("SELECT WHERE (simple predicates) partitioned") {
- assert(sql("SELECT * FROM parts WHERE THEID < 1").collect().size === 0)
- assert(sql("SELECT * FROM parts WHERE THEID != 2").collect().size === 2)
- assert(sql("SELECT THEID FROM parts WHERE THEID = 1").collect().size === 1)
+ val df1 = sql("SELECT * FROM parts WHERE THEID < 1")
+ checkNumPartitions(df1, expectedNumPartitions = 3)
+ assert(df1.collect().length === 0)
+
+ val df2 = sql("SELECT * FROM parts WHERE THEID != 2")
+ checkNumPartitions(df2, expectedNumPartitions = 3)
+ assert(df2.collect().length === 2)
+
+ val df3 = sql("SELECT THEID FROM parts WHERE THEID = 1")
+ checkNumPartitions(df3, expectedNumPartitions = 3)
+ assert(df3.collect().length === 1)
}
test("SELECT second field partitioned") {
@@ -370,24 +390,27 @@ class JDBCSuite extends SparkFunSuite
}
test("Partitioning via JDBCPartitioningInfo API") {
- assert(
- spark.read.jdbc(urlWithUserAndPass, "TEST.PEOPLE", "THEID", 0, 4, 3, new Properties())
- .collect().length === 3)
+ val df = spark.read.jdbc(urlWithUserAndPass, "TEST.PEOPLE", "THEID", 0, 4, 3, new Properties())
+ checkNumPartitions(df, expectedNumPartitions = 3)
+ assert(df.collect().length === 3)
}
test("Partitioning via list-of-where-clauses API") {
val parts = Array[String]("THEID < 2", "THEID >= 2")
- assert(spark.read.jdbc(urlWithUserAndPass, "TEST.PEOPLE", parts, new Properties())
- .collect().length === 3)
+ val df = spark.read.jdbc(urlWithUserAndPass, "TEST.PEOPLE", parts, new Properties())
+ checkNumPartitions(df, expectedNumPartitions = 2)
+ assert(df.collect().length === 3)
}
test("Partitioning on column that might have null values.") {
- assert(
- spark.read.jdbc(urlWithUserAndPass, "TEST.EMP", "theid", 0, 4, 3, new Properties())
- .collect().length === 4)
- assert(
- spark.read.jdbc(urlWithUserAndPass, "TEST.EMP", "THEID", 0, 4, 3, new Properties())
- .collect().length === 4)
+ val df = spark.read.jdbc(urlWithUserAndPass, "TEST.EMP", "theid", 0, 4, 3, new Properties())
+ checkNumPartitions(df, expectedNumPartitions = 3)
+ assert(df.collect().length === 4)
+
+ val df2 = spark.read.jdbc(urlWithUserAndPass, "TEST.EMP", "THEID", 0, 4, 3, new Properties())
+ checkNumPartitions(df2, expectedNumPartitions = 3)
+ assert(df2.collect().length === 4)
+
// partitioning on a nullable quoted column
assert(
spark.read.jdbc(urlWithUserAndPass, "TEST.EMP", """"Dept"""", 0, 4, 3, new Properties())
@@ -404,6 +427,7 @@ class JDBCSuite extends SparkFunSuite
numPartitions = 0,
connectionProperties = new Properties()
)
+ checkNumPartitions(res, expectedNumPartitions = 1)
assert(res.count() === 8)
}
@@ -417,6 +441,7 @@ class JDBCSuite extends SparkFunSuite
numPartitions = 10,
connectionProperties = new Properties()
)
+ checkNumPartitions(res, expectedNumPartitions = 4)
assert(res.count() === 8)
}
@@ -430,6 +455,7 @@ class JDBCSuite extends SparkFunSuite
numPartitions = 4,
connectionProperties = new Properties()
)
+ checkNumPartitions(res, expectedNumPartitions = 1)
assert(res.count() === 8)
}
@@ -450,7 +476,9 @@ class JDBCSuite extends SparkFunSuite
}
test("SELECT * on partitioned table with a nullable partition column") {
- assert(sql("SELECT * FROM nullparts").collect().size == 4)
+ val df = sql("SELECT * FROM nullparts")
+ checkNumPartitions(df, expectedNumPartitions = 3)
+ assert(df.collect().length == 4)
}
test("H2 integral types") {
@@ -722,7 +750,8 @@ class JDBCSuite extends SparkFunSuite
}
// test the JdbcRelation toString output
df.queryExecution.analyzed.collect {
- case r: LogicalRelation => assert(r.relation.toString == "JDBCRelation(TEST.PEOPLE)")
+ case r: LogicalRelation =>
+ assert(r.relation.toString == "JDBCRelation(TEST.PEOPLE) [numPartitions=3]")
}
}
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
index c834419948c530a588da56ad47e29ce43124bd95..064958bc1a14cbc713ea40b6551102ceef44cd02 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
@@ -319,9 +319,12 @@ class JDBCWriteSuite extends SharedSQLContext with BeforeAndAfter {
df.write.format("jdbc")
.option("dbtable", "TEST.SAVETEST")
.option("url", url1)
+ .option("user", "testUser")
+ .option("password", "testPass")
.option(s"${JDBCOptions.JDBC_NUM_PARTITIONS}", "0")
.save()
}.getMessage
- assert(e.contains("Invalid value `0` for parameter `numPartitions`. The minimum value is 1"))
+ assert(e.contains("Invalid value `0` for parameter `numPartitions` in table writing " +
+ "via JDBC. The minimum value is 1."))
}
}