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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@

package org.apache.spark.sql.execution.datasources.jdbc

import java.sql.{Connection, Driver, DriverManager, JDBCType, PreparedStatement, ResultSet, ResultSetMetaData, SQLException}
import java.sql.{Connection, Driver, DriverManager, JDBCType, PreparedStatement, ResultSet, ResultSetMetaData, SQLException, SQLFeatureNotSupportedException}
import java.util.Locale

import scala.collection.JavaConverters._
Expand All @@ -34,6 +34,7 @@ import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.SpecificInternalRow
import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
import org.apache.spark.sql.catalyst.util.{CaseInsensitiveMap, DateTimeUtils, GenericArrayData}
import org.apache.spark.sql.connector.catalog.TableChange
import org.apache.spark.sql.execution.datasources.jdbc.connection.ConnectionProvider
import org.apache.spark.sql.jdbc.{JdbcDialect, JdbcDialects, JdbcType}
import org.apache.spark.sql.types._
Expand Down Expand Up @@ -94,13 +95,7 @@ object JdbcUtils extends Logging {
* Drops a table from the JDBC database.
*/
def dropTable(conn: Connection, table: String, options: JDBCOptions): Unit = {
val statement = conn.createStatement
try {
statement.setQueryTimeout(options.queryTimeout)
statement.executeUpdate(s"DROP TABLE $table")
} finally {
statement.close()
}
executeStatement(conn, options, s"DROP TABLE $table")
}

/**
Expand Down Expand Up @@ -184,7 +179,7 @@ object JdbcUtils extends Logging {
}
}

private def getJdbcType(dt: DataType, dialect: JdbcDialect): JdbcType = {
private[sql] def getJdbcType(dt: DataType, dialect: JdbcDialect): JdbcType = {

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It's okay to remove private[sql] because execution is already in the private package (see also SPARK-16964)

dialect.getJDBCType(dt).orElse(getCommonJDBCType(dt)).getOrElse(
throw new IllegalArgumentException(s"Can't get JDBC type for ${dt.catalogString}"))
}
Expand Down Expand Up @@ -882,13 +877,7 @@ object JdbcUtils extends Logging {
// table_options or partition_options.
// E.g., "CREATE TABLE t (name string) ENGINE=InnoDB DEFAULT CHARSET=utf8"
val sql = s"CREATE TABLE $tableName ($strSchema) $createTableOptions"
val statement = conn.createStatement
try {
statement.setQueryTimeout(options.queryTimeout)
statement.executeUpdate(sql)
} finally {
statement.close()
}
executeStatement(conn, options, sql)
}

/**
Expand All @@ -900,10 +889,51 @@ object JdbcUtils extends Logging {
newTable: String,
options: JDBCOptions): Unit = {
val dialect = JdbcDialects.get(options.url)
executeStatement(conn, options, dialect.renameTable(oldTable, newTable))
}

/**
* Update a table from the JDBC database.
*/
def alterTable(
conn: Connection,
tableName: String,
changes: Seq[TableChange],
options: JDBCOptions): Unit = {
val dialect = JdbcDialects.get(options.url)
if (changes.length == 1) {
executeStatement(conn, options, dialect.alterTable(tableName, changes)(0))
} else {
val metadata = conn.getMetaData
if (!metadata.supportsTransactions) {
throw new SQLFeatureNotSupportedException("The target JDBC server does not support " +
"transaction and can only support ALTER TABLE with a single action.")
} else {
conn.setAutoCommit(false)
val statement = conn.createStatement
try {
statement.setQueryTimeout(options.queryTimeout)
for (sql <- dialect.alterTable(tableName, changes)) {
statement.executeUpdate(sql)
}
conn.commit()
} catch {
case e: Exception =>
if (conn != null) conn.rollback()
throw e
} finally {
statement.close()
conn.setAutoCommit(true)

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Should we record auto commit status and restore back?

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I guess we don't need to record the original auto commit status. The default value of autocommit is true.

}
}
}
}

private def executeStatement(conn: Connection, options: JDBCOptions, sql: String): Unit = {
val statement = conn.createStatement
try {
statement.setQueryTimeout(options.queryTimeout)
Comment on lines +923 to +935

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Other methods have similar code:

      val statement = ...
      try {
        statement.setQueryTimeout(options.queryTimeout)
        statement.execute ...
      } finally {
        statement.close()
      }

Could you put it to a private method.

statement.executeUpdate(dialect.renameTable(oldTable, newTable))
statement.executeUpdate(sql)
} finally {
statement.close()
}
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -129,11 +129,12 @@ class JDBCTableCatalog extends TableCatalog with Logging {
JDBCTable(ident, schema, writeOptions)
}

// TODO (SPARK-32402): Implement ALTER TABLE in JDBC Table Catalog
override def alterTable(ident: Identifier, changes: TableChange*): Table = {
// scalastyle:off throwerror
throw new NotImplementedError()
// scalastyle:on throwerror
checkNamespace(ident.namespace())
withConnection { conn =>
JdbcUtils.alterTable(conn, getTableName(ident), changes, options)
loadTable(ident)
}
}

private def checkNamespace(namespace: Array[String]): Unit = {
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -17,11 +17,16 @@

package org.apache.spark.sql.jdbc

import java.sql.{Connection, Date, Timestamp}
import java.sql.{Connection, Date, SQLFeatureNotSupportedException, Timestamp}

import scala.collection.mutable.ArrayBuilder

import org.apache.commons.lang3.StringUtils

import org.apache.spark.annotation.{DeveloperApi, Since}
import org.apache.spark.sql.connector.catalog.TableChange
import org.apache.spark.sql.connector.catalog.TableChange._
import org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils
import org.apache.spark.sql.types._

/**
Expand Down Expand Up @@ -184,15 +189,61 @@ abstract class JdbcDialect extends Serializable {
/**
* Rename an existing table.
*
* TODO (SPARK-32382): Override this method in the dialects that don't support such syntax.
*
* @param oldTable The existing table.
* @param newTable New name of the table.
* @return The SQL statement to use for renaming the table.
*/
def renameTable(oldTable: String, newTable: String): String = {
s"ALTER TABLE $oldTable RENAME TO $newTable"
}

/**
* Alter an existing table.
* TODO (SPARK-32523): Override this method in the dialects that have different syntax.

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Because you will override this method in other places, not here. Remember to remove this later. :)

*
* @param tableName The name of the table to be altered.
* @param changes Changes to apply to the table.
* @return The SQL statements to use for altering the table.
*/
def alterTable(tableName: String, changes: Seq[TableChange]): Array[String] = {
val updateClause = ArrayBuilder.make[String]
for (change <- changes) {
change match {
case add: AddColumn if add.fieldNames.length == 1 =>
add.fieldNames match {
case Array(name) =>

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we should have a better error message if the field name has more than one parts.

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Seems to me fieldName always has only one element.

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If we do believe it always has one element, maybe add an assert?

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People can alter a nested field, that why the type of fieldNames is Array[String]. e.g. ALTER TABLE t RENAME COLUMN a.b TO c

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Does this look OK?

            case _ =>
              throw new SQLFeatureNotSupportedException("Nested column is not supported.")

@cloud-fan cloud-fan Aug 4, 2020

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add.fieldNames match {
            case Array(name) =>

We will fail at this pattern match.

One way is

case add: AddColumn if add.fieldNames.length == 1 =>

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@cloud-fan I changed code to what you suggested.
We don't support nested column in JDBC yet. In JdbcUtils.getCatalystType, we map java.sql.Types.STRUCT => StringType. In getCommonJDBCType, we don't have a match case for StructType and the default is None. Seems to me currently it is not possible to reach the code path of multiple parts fieldNames in JdbcDialects.alterTable, so I will not have a negative test case for this code path for now.

val dataType = JdbcUtils.getJdbcType(add.dataType(), this).databaseTypeDefinition
updateClause += s"ALTER TABLE $tableName ADD COLUMN $name $dataType"
}
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Outdated
case rename: RenameColumn if rename.fieldNames.length == 1 =>
rename.fieldNames match {
case Array(name) =>
updateClause += s"ALTER TABLE $tableName RENAME COLUMN $name TO ${rename.newName}"
}
case delete: DeleteColumn if delete.fieldNames.length == 1 =>
delete.fieldNames match {
case Array(name) =>
updateClause += s"ALTER TABLE $tableName DROP COLUMN $name"
}
case update: UpdateColumnType if update.fieldNames.length == 1 =>
update.fieldNames match {
case Array(name) =>
val dataType = JdbcUtils.getJdbcType(update.newDataType(), this)

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nit: We know fieldNames must be one element now. We don't need match and can just access fieldNames(0).

.databaseTypeDefinition
updateClause += s"ALTER TABLE $tableName ALTER COLUMN $name $dataType"
}
case update: UpdateColumnNullability if update.fieldNames.length == 1 =>
update.fieldNames match {
case Array(name) =>
val nullable = if (update.nullable()) "NULL" else "NOT NULL"
updateClause += s"ALTER TABLE $tableName ALTER COLUMN $name SET $nullable"
}
case _ =>
throw new SQLFeatureNotSupportedException(s"Unsupported TableChange $change")
}
}
updateClause.result()
}
}

/**
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ import java.util.Properties
import org.apache.spark.SparkConf
import org.apache.spark.sql.{QueryTest, Row}
import org.apache.spark.sql.test.SharedSparkSession
import org.apache.spark.sql.types.{IntegerType, StringType, StructType}
import org.apache.spark.sql.types._
import org.apache.spark.util.Utils

class JDBCTableCatalogSuite extends QueryTest with SharedSparkSession {
Expand Down Expand Up @@ -106,4 +106,71 @@ class JDBCTableCatalogSuite extends QueryTest with SharedSparkSession {
Seq(Row("test", "people"), Row("test", "new_table")))
}
}

test("alter table ... add column") {
withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (ID INTEGER) USING _")
sql("ALTER TABLE h2.test.alt_table ADD COLUMNS (C1 INTEGER, C2 STRING)")
var t = spark.table("h2.test.alt_table")
var expectedSchema = new StructType()
.add("ID", IntegerType)
.add("C1", IntegerType)
.add("C2", StringType)
assert(t.schema === expectedSchema)
sql("ALTER TABLE h2.test.alt_table ADD COLUMNS (C3 DOUBLE)")
t = spark.table("h2.test.alt_table")
expectedSchema = expectedSchema.add("C3", DoubleType)
assert(t.schema === expectedSchema)

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I think it's better to compare schemas than my previous method to use DESCRIBE TABLE.

}
}

test("alter table ... rename column") {
withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (ID INTEGER) USING _")
sql("ALTER TABLE h2.test.alt_table RENAME COLUMN ID TO C")
val t = spark.table("h2.test.alt_table")
val expectedSchema = new StructType().add("C", IntegerType)
assert(t.schema === expectedSchema)
}
}

test("alter table ... drop column") {
withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (C1 INTEGER, C2 INTEGER) USING _")
sql("ALTER TABLE h2.test.alt_table DROP COLUMN C1")
val t = spark.table("h2.test.alt_table")
val expectedSchema = new StructType().add("C2", IntegerType)
assert(t.schema === expectedSchema)
}
}

test("alter table ... update column type") {
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withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (ID INTEGER) USING _")
sql("ALTER TABLE h2.test.alt_table ALTER COLUMN id TYPE DOUBLE")
val t = spark.table("h2.test.alt_table")
val expectedSchema = new StructType().add("ID", DoubleType)
assert(t.schema === expectedSchema)
}
}

test("alter table ... update column nullability") {
withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (ID INTEGER NOT NULL) USING _")
sql("ALTER TABLE h2.test.alt_table ALTER COLUMN ID DROP NOT NULL")
val t = spark.table("h2.test.alt_table")
val expectedSchema = new StructType().add("ID", IntegerType, nullable = true)
assert(t.schema === expectedSchema)
}
}

test("alter table ... update column comment not supported") {
withTable("h2.test.alt_table") {
sql("CREATE TABLE h2.test.alt_table (ID INTEGER) USING _")
val thrown = intercept[java.sql.SQLFeatureNotSupportedException] {
sql("ALTER TABLE h2.test.alt_table ALTER COLUMN ID COMMENT 'test'")
}
assert(thrown.getMessage.contains("Unsupported TableChange"))
}
}
}