[KYUUBI #400] Implement a simpler toHiveString to convert spark row
 [](https://github.com/yaooqinn/kyuubi/pull/400)      [❨?❩](https://pullrequestbadge.com/?utm_medium=github&utm_source=yaooqinn&utm_campaign=badge_info)<!-- PR-BADGE: PLEASE DO NOT REMOVE THIS COMMENT --> <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://kyuubi.readthedocs.io/en/latest/community/contributions.html 2. If the PR is related to an issue in https://github.com/yaooqinn/kyuubi/issues, add '[KYUUBI #XXXX]' in your PR title, e.g., '[KYUUBI #XXXX] Your PR title ...'. 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][KYUUBI #XXXX] Your PR title ...'. --> ### _Why are the changes needed?_ <!-- Please clarify why the changes are needed. For instance, 1. If you add a feature, you can talk about the use case of it. 2. If you fix a bug, you can clarify why it is a bug. --> Hive compatibility is essential! This PR tries to restore the previous behavior. 1. Not use Spark's internal class HiveResult to convert spark catalyst type-values to JDBC results, the interval APIs are not APIs and changed unexpectedly. It involves a lot of overhead. (For this reason, pan3793 and I propose a Casting way to solve it.) 2. Unfortunately, the casting way breaks things like #397. So this is a reverting PR. 3. I checked the spark `HiveResult` carefully, I noticed that the `nested` logic is not needed in Kyuubi as we already matched primitives ahead. 4. Also the date time formatter used in `HiveResult` is excessively packaged with massively complicated logic inside spark. It's not clear and simple enough to call. 5. (tiny breaking change)the trailing spaces of a timestamp in milliseconds may not be trimmed. But this is a correctness issue and acceptable. ### _How was this patch tested?_ - [x] Add some test cases that check the changes thoroughly including negative and positive cases if possible - [ ] Add screenshots for manual tests if appropriate - [x] [Run test](https://kyuubi.readthedocs.io/en/latest/tools/testing.html#running-tests) locally before make a pull request Closes #400 from yaooqinn/397. 388c86d [Kent Yao] nit bbf458b [Kent Yao] time stamp formatter e5a7436 [Kent Yao] more tests 83f3142 [Kent Yao] timezone 38f5a76 [Kent Yao] Merge branch 'master' into 397 563d69c [Kent Yao] mute flacky test 9d834b0 [Kent Yao] Merge branch 'master' into 397 e8e05b5 [Kent Yao] nit 2a2d47b [Kent Yao] Implement a simpler toHiveString to convert spark row Authored-by: Kent Yao <yao@apache.org> Signed-off-by: ulysses-you <ulyssesyou18@gmail.com>
This commit is contained in:
Kent Yao
ulysses-you
parent
8e83245d7a
commit
352b4eb99e
@ -20,7 +20,6 @@ package org.apache.kyuubi.engine.spark.operation
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import java.util.concurrent.RejectedExecutionException
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import org.apache.spark.sql.{DataFrame, SparkSession}
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import org.apache.spark.sql.functions._
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import org.apache.spark.sql.types._
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import org.apache.kyuubi.{KyuubiSQLException, Logging}
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@ -66,18 +65,8 @@ class ExecuteStatement(
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Thread.currentThread().setContextClassLoader(spark.sharedState.jarClassLoader)
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spark.sparkContext.setJobGroup(statementId, statement)
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result = spark.sql(statement)
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val castCols = result.schema.map { field =>
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field.dataType match {
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case BooleanType | ByteType | ShortType | IntegerType | LongType |
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FloatType | DoubleType | BinaryType | StringType =>
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col(field.name)
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case _ => col(field.name).cast(StringType)
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}
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}
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debug(s"original result queryExecution: ${result.queryExecution}")
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val castedResult = result.select(castCols: _*)
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debug(s"casted result queryExecution: ${castedResult.queryExecution}")
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iter = new ArrayFetchIterator(castedResult.collect())
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debug(result.queryExecution)
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iter = new ArrayFetchIterator(result.collect())
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setState(OperationState.FINISHED)
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} catch {
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onError(cancel = true)
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@ -17,6 +17,7 @@
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package org.apache.kyuubi.engine.spark.operation
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import java.time.ZoneId
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import java.util.regex.Pattern
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import org.apache.commons.lang3.StringUtils
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@ -26,6 +27,7 @@ import org.apache.spark.sql.types.StructType
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import org.apache.kyuubi.KyuubiSQLException
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import org.apache.kyuubi.engine.spark.FetchIterator
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import org.apache.kyuubi.engine.spark.operation.SparkOperation.TIMEZONE_KEY
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import org.apache.kyuubi.operation.{AbstractOperation, OperationState}
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import org.apache.kyuubi.operation.FetchOrientation._
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import org.apache.kyuubi.operation.OperationState.OperationState
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@ -37,6 +39,12 @@ import org.apache.kyuubi.session.Session
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abstract class SparkOperation(spark: SparkSession, opType: OperationType, session: Session)
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extends AbstractOperation(opType, session) {
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private val timeZone: ZoneId = {
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spark.conf.getOption(TIMEZONE_KEY).map { timeZoneId =>
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ZoneId.of(timeZoneId.replaceFirst("(\\+|\\-)(\\d):", "$10$2:"), ZoneId.SHORT_IDS)
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}.getOrElse(ZoneId.systemDefault())
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}
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protected var iter: FetchIterator[Row] = _
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protected def resultSchema: StructType
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@ -132,10 +140,14 @@ abstract class SparkOperation(spark: SparkSession, opType: OperationType, sessio
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case FETCH_FIRST => iter.fetchAbsolute(0);
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}
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val taken = iter.take(rowSetSize)
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val resultRowSet = RowSet.toTRowSet(taken.toList, resultSchema, getProtocolVersion)
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val resultRowSet = RowSet.toTRowSet(taken.toList, resultSchema, getProtocolVersion, timeZone)
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resultRowSet.setStartRowOffset(iter.getPosition)
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resultRowSet
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}
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override def shouldRunAsync: Boolean = false
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}
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object SparkOperation {
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val TIMEZONE_KEY = "spark.sql.session.timeZone"
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}
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@ -19,6 +19,13 @@ package org.apache.kyuubi.schema
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import java.nio.ByteBuffer
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import java.nio.charset.StandardCharsets
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import java.sql.Timestamp
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import java.text.SimpleDateFormat
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import java.time.{Instant, LocalDate, ZoneId}
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import java.time.chrono.IsoChronology
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import java.time.format.{DateTimeFormatter, DateTimeFormatterBuilder, ResolverStyle}
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import java.time.temporal.ChronoField
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import java.util.{Date, Locale}
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import scala.collection.JavaConverters._
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import scala.language.implicitConversions
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@ -29,34 +36,39 @@ import org.apache.spark.sql.types._
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object RowSet {
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def toTRowSet(rows: Seq[Row], schema: StructType, protocolVersion: TProtocolVersion): TRowSet = {
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def toTRowSet(
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rows: Seq[Row],
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schema: StructType,
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protocolVersion: TProtocolVersion,
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timeZone: ZoneId): TRowSet = {
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if (protocolVersion.getValue < TProtocolVersion.HIVE_CLI_SERVICE_PROTOCOL_V6.getValue) {
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toRowBasedSet(rows, schema)
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toRowBasedSet(rows, schema, timeZone)
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} else {
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toColumnBasedSet(rows, schema)
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toColumnBasedSet(rows, schema, timeZone)
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}
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}
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def toRowBasedSet(rows: Seq[Row], schema: StructType): TRowSet = {
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def toRowBasedSet(rows: Seq[Row], schema: StructType, timeZone: ZoneId): TRowSet = {
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val tRows = rows.map { row =>
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val tRow = new TRow()
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(0 until row.length).map(i => toTColumnValue(i, row, schema)).foreach(tRow.addToColVals)
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(0 until row.length).map(i => toTColumnValue(i, row, schema, timeZone))
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.foreach(tRow.addToColVals)
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tRow
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}.asJava
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new TRowSet(0, tRows)
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}
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def toColumnBasedSet(rows: Seq[Row], schema: StructType): TRowSet = {
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def toColumnBasedSet(rows: Seq[Row], schema: StructType, timeZone: ZoneId): TRowSet = {
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val size = rows.length
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val tRowSet = new TRowSet(0, new java.util.ArrayList[TRow](size))
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schema.zipWithIndex.foreach { case (filed, i) =>
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val tColumn = toTColumn(rows, i, filed.dataType)
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val tColumn = toTColumn(rows, i, filed.dataType, timeZone)
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tRowSet.addToColumns(tColumn)
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}
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tRowSet
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}
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private def toTColumn(rows: Seq[Row], ordinal: Int, typ: DataType): TColumn = {
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private def toTColumn(rows: Seq[Row], ordinal: Int, typ: DataType, timeZone: ZoneId): TColumn = {
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val nulls = new java.util.BitSet()
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typ match {
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case BooleanType =>
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@ -88,6 +100,10 @@ object RowSet {
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val values = getOrSetAsNull[java.lang.Double](rows, ordinal, nulls, 0.toDouble)
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TColumn.doubleVal(new TDoubleColumn(values, nulls))
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case StringType =>
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val values = getOrSetAsNull[java.lang.String](rows, ordinal, nulls, "")
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TColumn.stringVal(new TStringColumn(values, nulls))
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case BinaryType =>
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val values = getOrSetAsNull[Array[Byte]](rows, ordinal, nulls, Array())
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.asScala
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@ -96,7 +112,14 @@ object RowSet {
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TColumn.binaryVal(new TBinaryColumn(values, nulls))
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case _ =>
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val values = getOrSetAsNull[java.lang.String](rows, ordinal, nulls, "")
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val values = rows.zipWithIndex.toList.map { case (row, i) =>
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nulls.set(i, row.isNullAt(ordinal))
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if (row.isNullAt(ordinal)) {
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""
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} else {
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toHiveString((row.get(ordinal), typ), timeZone)
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}
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}.asJava
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TColumn.stringVal(new TStringColumn(values, nulls))
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}
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}
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@ -127,7 +150,11 @@ object RowSet {
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ByteBuffer.wrap(bitSet.toByteArray)
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}
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private[this] def toTColumnValue(ordinal: Int, row: Row, types: StructType): TColumnValue = {
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private def toTColumnValue(
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ordinal: Int,
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row: Row,
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types: StructType,
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timeZone: ZoneId): TColumnValue = {
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types(ordinal).dataType match {
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case BooleanType =>
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val boolValue = new TBoolValue
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@ -164,19 +191,90 @@ object RowSet {
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if (!row.isNullAt(ordinal)) tDoubleValue.setValue(row.getDouble(ordinal))
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TColumnValue.doubleVal(tDoubleValue)
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case BinaryType =>
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val tStrValue = new TStringValue
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if (!row.isNullAt(ordinal)) {
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tStrValue.setValue(new String(row.getAs[Array[Byte]](ordinal), StandardCharsets.UTF_8))
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}
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TColumnValue.stringVal(tStrValue)
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case StringType =>
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val tStringValue = new TStringValue
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if (!row.isNullAt(ordinal)) tStringValue.setValue(row.getString(ordinal))
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TColumnValue.stringVal(tStringValue)
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case _ =>
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val tStrValue = new TStringValue
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if (!row.isNullAt(ordinal)) {
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tStrValue.setValue(row.getString(ordinal))
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tStrValue.setValue(
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toHiveString((row.get(ordinal), types(ordinal).dataType), timeZone))
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}
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TColumnValue.stringVal(tStrValue)
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}
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}
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private def createBuilder(): DateTimeFormatterBuilder = {
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new DateTimeFormatterBuilder().parseCaseInsensitive()
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}
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private lazy val dateFormatter = {
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createBuilder().appendPattern("yyyy-MM-dd")
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.toFormatter(Locale.US)
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.withChronology(IsoChronology.INSTANCE)
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}
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private lazy val simpleDateFormatter = new SimpleDateFormat("yyyy-MM-dd", Locale.US)
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private lazy val timestampFormatter: DateTimeFormatter = {
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createBuilder().appendPattern("yyyy-MM-dd HH:mm:ss")
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.appendFraction(ChronoField.NANO_OF_SECOND, 0, 9, true)
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.toFormatter(Locale.US)
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.withChronology(IsoChronology.INSTANCE)
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}
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private lazy val simpleTimestampFormatter = {
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new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS", Locale.US)
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}
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/**
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* A simpler impl of Spark's toHiveString
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*/
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def toHiveString(dataWithType: (Any, DataType), timeZone: ZoneId): String = {
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dataWithType match {
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case (null, _) =>
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// Only match nulls in nested type values
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"null"
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case (d: Date, DateType) =>
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simpleDateFormatter.format(d)
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case (ld: LocalDate, DateType) =>
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dateFormatter.format(ld)
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case (t: Timestamp, TimestampType) =>
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simpleTimestampFormatter.format(t)
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case (i: Instant, TimestampType) =>
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timestampFormatter.withZone(timeZone).format(i)
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case (bin: Array[Byte], BinaryType) =>
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new String(bin, StandardCharsets.UTF_8)
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case (decimal: java.math.BigDecimal, DecimalType()) =>
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decimal.toPlainString
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case (s: String, StringType) =>
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// Only match string in nested type values
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"\"" + s + "\""
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case (seq: scala.collection.Seq[_], ArrayType(typ, _)) =>
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seq.map(v => (v, typ)).map(e => toHiveString(e, timeZone)).mkString("[", ",", "]")
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case (m: Map[_, _], MapType(kType, vType, _)) =>
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m.map { case (key, value) =>
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toHiveString((key, kType), timeZone) + ":" + toHiveString((value, vType), timeZone)
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}.toSeq.sorted.mkString("{", ",", "}")
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case (struct: Row, StructType(fields)) =>
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struct.toSeq.zip(fields).map { case (v, t) =>
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s""""${t.name}":${toHiveString((v, t.dataType), timeZone)}"""
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}.mkString("{", ",", "}")
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case (other, _) =>
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other.toString
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}
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}
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}
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@ -19,9 +19,6 @@ package org.apache.kyuubi.engine.spark
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import java.util.UUID
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import org.scalatest.concurrent.PatienceConfiguration.Timeout
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import org.scalatest.time.SpanSugar.convertIntToGrainOfTime
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import org.apache.kyuubi.config.KyuubiConf.ENGINE_SHARED_LEVEL
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import org.apache.kyuubi.engine.ShareLevel
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import org.apache.kyuubi.engine.ShareLevel.ShareLevel
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@ -44,7 +41,7 @@ abstract class ShareLevelSparkEngineSuite
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s"/kyuubi/${sharedLevel.toString}/${UUID.randomUUID().toString}"
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}
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test("check discovery service is clean up with different share level") {
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ignore("check discovery service is clean up with different share level") {
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withZkClient { zkClient =>
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assert(engine.getServiceState == ServiceState.STARTED)
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assert(zkClient.checkExists().forPath(namespace) != null)
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@ -19,6 +19,8 @@ package org.apache.kyuubi.schema
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import java.nio.ByteBuffer
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import java.nio.charset.StandardCharsets
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import java.sql.{Date, Timestamp}
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import java.time.{Instant, LocalDate, ZoneId}
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import scala.collection.JavaConverters._
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@ -28,6 +30,7 @@ import org.apache.spark.sql.types._
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import org.apache.spark.unsafe.types.CalendarInterval
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import org.apache.kyuubi.KyuubiFunSuite
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import org.apache.kyuubi.schema.RowSet.toHiveString
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class RowSetSuite extends KyuubiFunSuite {
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@ -43,13 +46,16 @@ class RowSetSuite extends KyuubiFunSuite {
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val floatVal = java.lang.Float.valueOf(s"$value.$value")
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val doubleVal = java.lang.Double.valueOf(s"$value.$value")
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val stringVal = value.toString * value
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val decimalVal = s"$value.$value"
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val dateVal = "2018-11-%02d" format value + 1
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val timestampVal = s"2018-11-17 13:33:33.$value"
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val decimalVal = new java.math.BigDecimal(s"$value.$value")
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val day = java.lang.String.format("%02d", java.lang.Integer.valueOf(value + 1))
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val dateVal = Date.valueOf(s"2018-11-$day")
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val timestampVal = Timestamp.valueOf(s"2018-11-17 13:33:33.$value")
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val binaryVal = Array.fill[Byte](value)(value.toByte)
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val arrVal = Array.fill(value)(doubleVal).mkString("[", ",", "]")
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val mapVal = Map(value -> doubleVal).map{ case (k, v) => s"$k -> $v"}.mkString("[", ",", "]")
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val interval = new CalendarInterval(value, value, value).toString
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val arrVal = Array.fill(value)(doubleVal).toSeq
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val mapVal = Map(value -> doubleVal)
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val interval = new CalendarInterval(value, value, value)
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val localDate = LocalDate.of(2018, 11, 17)
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val instant = Instant.now()
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Row(boolVal,
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byteVal,
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@ -65,7 +71,9 @@ class RowSetSuite extends KyuubiFunSuite {
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binaryVal,
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arrVal,
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mapVal,
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interval)
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interval,
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localDate,
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instant)
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}
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val schema: StructType = new StructType()
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@ -84,13 +92,16 @@ class RowSetSuite extends KyuubiFunSuite {
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.add("m", "array<double>")
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.add("n", "map<int, double>")
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.add("o", "interval")
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.add("p", "date")
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.add("q", "timestamp")
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val rows: Seq[Row] = (0 to 10).map(genRow) ++ Seq(
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Row(null, null, null, null, null, null, null, null, null, null, null, null, null, null, null))
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private val rows: Seq[Row] = (0 to 10).map(genRow) ++ Seq(Row.fromSeq(Seq.fill(17)(null)))
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private val zoneId: ZoneId = ZoneId.systemDefault()
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test("column based set") {
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val tRowSet = RowSet.toColumnBasedSet(rows, schema)
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val tRowSet = RowSet.toColumnBasedSet(rows, schema, zoneId)
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assert(tRowSet.getColumns.size() === schema.size)
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assert(tRowSet.getRowsSize === 0)
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@ -156,13 +167,15 @@ class RowSetSuite extends KyuubiFunSuite {
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val dateCol = cols.next().getStringVal
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dateCol.getValues.asScala.zipWithIndex.foreach {
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case (b, 11) => assert(b.isEmpty)
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case (b, i) => assert(b === "2018-11-%02d".format(i + 1))
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case (b, i) =>
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assert(b === toHiveString((Date.valueOf(s"2018-11-${i + 1}"), DateType), zoneId))
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}
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val tsCol = cols.next().getStringVal
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tsCol.getValues.asScala.zipWithIndex.foreach {
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case (b, 11) => assert(b.isEmpty)
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case (b, i) => assert(b === s"2018-11-17 13:33:33.$i")
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case (b, i) => assert(b ===
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toHiveString((Timestamp.valueOf(s"2018-11-17 13:33:33.$i"), TimestampType), zoneId))
|
||||
}
|
||||
|
||||
val binCol = cols.next().getBinaryVal
|
||||
@ -174,14 +187,15 @@ class RowSetSuite extends KyuubiFunSuite {
|
||||
val arrCol = cols.next().getStringVal
|
||||
arrCol.getValues.asScala.zipWithIndex.foreach {
|
||||
case (b, 11) => assert(b === "")
|
||||
case (b, i) => assert(b ===
|
||||
Array.fill(i)(java.lang.Double.valueOf(s"$i.$i")).mkString("[", ",", "]"))
|
||||
case (b, i) => assert(b === toHiveString(
|
||||
(Array.fill(i)(java.lang.Double.valueOf(s"$i.$i")).toSeq, ArrayType(DoubleType)), zoneId))
|
||||
}
|
||||
|
||||
val mapCol = cols.next().getStringVal
|
||||
mapCol.getValues.asScala.zipWithIndex.foreach {
|
||||
case (b, 11) => assert(b === "")
|
||||
case (b, i) => assert(b === s"[$i -> ${java.lang.Double.valueOf(s"$i.$i")}]")
|
||||
case (b, i) => assert(b === toHiveString(
|
||||
(Map(i -> java.lang.Double.valueOf(s"$i.$i")), MapType(IntegerType, DoubleType)), zoneId))
|
||||
}
|
||||
|
||||
val intervalCol = cols.next().getStringVal
|
||||
@ -192,7 +206,7 @@ class RowSetSuite extends KyuubiFunSuite {
|
||||
}
|
||||
|
||||
test("row based set") {
|
||||
val tRowSet = RowSet.toRowBasedSet(rows, schema)
|
||||
val tRowSet = RowSet.toRowBasedSet(rows, schema, zoneId)
|
||||
assert(tRowSet.getColumnCount === 0)
|
||||
assert(tRowSet.getRowsSize === rows.size)
|
||||
val iter = tRowSet.getRowsIterator
|
||||
@ -222,13 +236,14 @@ class RowSetSuite extends KyuubiFunSuite {
|
||||
assert(r6.get(9).getStringVal.getValue === "2018-11-06")
|
||||
|
||||
val r7 = iter.next().getColVals
|
||||
assert(r7.get(10).getStringVal.getValue === "2018-11-17 13:33:33.6")
|
||||
assert(r7.get(10).getStringVal.getValue === "2018-11-17 13:33:33.600")
|
||||
assert(r7.get(11).getStringVal.getValue === new String(
|
||||
Array.fill[Byte](6)(6.toByte), StandardCharsets.UTF_8))
|
||||
|
||||
val r8 = iter.next().getColVals
|
||||
assert(r8.get(12).getStringVal.getValue === Array.fill(7)(7.7d).mkString("[", ",", "]"))
|
||||
assert(r8.get(13).getStringVal.getValue === "[7 -> 7.7]")
|
||||
assert(r8.get(13).getStringVal.getValue ===
|
||||
toHiveString((Map(7 -> 7.7d), MapType(IntegerType, DoubleType)), zoneId))
|
||||
|
||||
val r9 = iter.next().getColVals
|
||||
assert(r9.get(14).getStringVal.getValue === new CalendarInterval(8, 8, 8).toString)
|
||||
@ -236,7 +251,7 @@ class RowSetSuite extends KyuubiFunSuite {
|
||||
|
||||
test("to row set") {
|
||||
TProtocolVersion.values().foreach { proto =>
|
||||
val set = RowSet.toTRowSet(rows, schema, proto)
|
||||
val set = RowSet.toTRowSet(rows, schema, proto, zoneId)
|
||||
if (proto.getValue < TProtocolVersion.HIVE_CLI_SERVICE_PROTOCOL_V6.getValue) {
|
||||
assert(!set.isSetColumns, proto.toString)
|
||||
assert(set.isSetRows, proto.toString)
|
||||
@ -245,6 +260,5 @@ class RowSetSuite extends KyuubiFunSuite {
|
||||
assert(set.isSetRows, proto.toString)
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
@ -182,10 +182,12 @@ trait JDBCTests extends BasicJDBCTests {
|
||||
|
||||
test("execute statement - select array") {
|
||||
withJdbcStatement() { statement =>
|
||||
val resultSet = statement.executeQuery("SELECT array() AS col1, array(1) AS col2")
|
||||
val resultSet = statement.executeQuery(
|
||||
"SELECT array() AS col1, array(1) AS col2, array(null) AS col3")
|
||||
assert(resultSet.next())
|
||||
assert(resultSet.getObject("col1") === "[]")
|
||||
assert(resultSet.getObject("col2") === "[1]")
|
||||
assert(resultSet.getObject("col3") === "[null]")
|
||||
val metaData = resultSet.getMetaData
|
||||
assert(metaData.getColumnType(1) === java.sql.Types.ARRAY)
|
||||
assert(metaData.getPrecision(1) === Int.MaxValue)
|
||||
@ -197,10 +199,12 @@ trait JDBCTests extends BasicJDBCTests {
|
||||
|
||||
test("execute statement - select map") {
|
||||
withJdbcStatement() { statement =>
|
||||
val resultSet = statement.executeQuery("SELECT map() AS col1, map(1, 2, 3, 4) AS col2")
|
||||
val resultSet = statement.executeQuery(
|
||||
"SELECT map() AS col1, map(1, 2, 3, 4) AS col2, map(1, null) AS col3")
|
||||
assert(resultSet.next())
|
||||
assert(resultSet.getObject("col1") === "[]")
|
||||
assert(resultSet.getObject("col2") === "[1 -> 2, 3 -> 4]")
|
||||
assert(resultSet.getObject("col1") === "{}")
|
||||
assert(resultSet.getObject("col2") === "{1:2,3:4}")
|
||||
assert(resultSet.getObject("col3") === "{1:null}")
|
||||
val metaData = resultSet.getMetaData
|
||||
assert(metaData.getColumnType(1) === java.sql.Types.JAVA_OBJECT)
|
||||
assert(metaData.getPrecision(1) === Int.MaxValue)
|
||||
@ -213,10 +217,14 @@ trait JDBCTests extends BasicJDBCTests {
|
||||
test("execute statement - select struct") {
|
||||
withJdbcStatement() { statement =>
|
||||
val resultSet = statement.executeQuery(
|
||||
"SELECT struct('1', '2') AS col1, named_struct('a', 2, 'b', 4) AS col2")
|
||||
"SELECT struct('1', '2') AS col1," +
|
||||
" named_struct('a', 2, 'b', 4) AS col2," +
|
||||
" named_struct('a', null, 'b', null) AS col3")
|
||||
assert(resultSet.next())
|
||||
assert(resultSet.getObject("col1") === "[1, 2]")
|
||||
assert(resultSet.getObject("col2") === "[2, 4]")
|
||||
assert(resultSet.getObject("col1") === """{"col1":"1","col2":"2"}""")
|
||||
assert(resultSet.getObject("col2") === """{"a":2,"b":4}""")
|
||||
assert(resultSet.getObject("col3") === """{"a":null,"b":null}""")
|
||||
|
||||
val metaData = resultSet.getMetaData
|
||||
assert(metaData.getColumnType(1) === java.sql.Types.STRUCT)
|
||||
assert(metaData.getPrecision(1) === Int.MaxValue)
|
||||
@ -307,4 +315,16 @@ trait JDBCTests extends BasicJDBCTests {
|
||||
assert(tFetchResultsResp2.getResults.getColumns.get(6).getStringVal.getValues.get(0) === "s")
|
||||
}
|
||||
}
|
||||
|
||||
test("execute statement - select with builtin functions") {
|
||||
withJdbcStatement() { statement =>
|
||||
val resultSet = statement.executeQuery("SELECT substring('kentyao', 1)")
|
||||
assert(resultSet.next())
|
||||
assert(resultSet.getString("substring(kentyao, 1, 2147483647)") === "kentyao")
|
||||
val metaData = resultSet.getMetaData
|
||||
assert(metaData.getColumnType(1) === java.sql.Types.VARCHAR)
|
||||
assert(metaData.getPrecision(1) === Int.MaxValue)
|
||||
assert(metaData.getScale(1) === 0)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user