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Revert "[SPARK-23096][SS] Migrate rate source to V2"
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sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/RateSourceProvider.scala
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.execution.streaming | ||
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| import java.io._ | ||
| import java.nio.charset.StandardCharsets | ||
| import java.util.Optional | ||
| import java.util.concurrent.TimeUnit | ||
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| import org.apache.commons.io.IOUtils | ||
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| import org.apache.spark.internal.Logging | ||
| import org.apache.spark.network.util.JavaUtils | ||
| import org.apache.spark.sql.{AnalysisException, DataFrame, SQLContext} | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.util.{CaseInsensitiveMap, DateTimeUtils} | ||
| import org.apache.spark.sql.execution.streaming.continuous.RateStreamContinuousReader | ||
| import org.apache.spark.sql.sources.{DataSourceRegister, StreamSourceProvider} | ||
| import org.apache.spark.sql.sources.v2._ | ||
| import org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader | ||
| import org.apache.spark.sql.types._ | ||
| import org.apache.spark.util.{ManualClock, SystemClock} | ||
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| /** | ||
| * A source that generates increment long values with timestamps. Each generated row has two | ||
| * columns: a timestamp column for the generated time and an auto increment long column starting | ||
| * with 0L. | ||
| * | ||
| * This source supports the following options: | ||
| * - `rowsPerSecond` (e.g. 100, default: 1): How many rows should be generated per second. | ||
| * - `rampUpTime` (e.g. 5s, default: 0s): How long to ramp up before the generating speed | ||
| * becomes `rowsPerSecond`. Using finer granularities than seconds will be truncated to integer | ||
| * seconds. | ||
| * - `numPartitions` (e.g. 10, default: Spark's default parallelism): The partition number for the | ||
| * generated rows. The source will try its best to reach `rowsPerSecond`, but the query may | ||
| * be resource constrained, and `numPartitions` can be tweaked to help reach the desired speed. | ||
| */ | ||
| class RateSourceProvider extends StreamSourceProvider with DataSourceRegister | ||
| with DataSourceV2 with ContinuousReadSupport { | ||
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| override def sourceSchema( | ||
| sqlContext: SQLContext, | ||
| schema: Option[StructType], | ||
| providerName: String, | ||
| parameters: Map[String, String]): (String, StructType) = { | ||
| if (schema.nonEmpty) { | ||
| throw new AnalysisException("The rate source does not support a user-specified schema.") | ||
| } | ||
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| (shortName(), RateSourceProvider.SCHEMA) | ||
| } | ||
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| override def createSource( | ||
| sqlContext: SQLContext, | ||
| metadataPath: String, | ||
| schema: Option[StructType], | ||
| providerName: String, | ||
| parameters: Map[String, String]): Source = { | ||
| val params = CaseInsensitiveMap(parameters) | ||
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| val rowsPerSecond = params.get("rowsPerSecond").map(_.toLong).getOrElse(1L) | ||
| if (rowsPerSecond <= 0) { | ||
| throw new IllegalArgumentException( | ||
| s"Invalid value '${params("rowsPerSecond")}'. The option 'rowsPerSecond' " + | ||
| "must be positive") | ||
| } | ||
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| val rampUpTimeSeconds = | ||
| params.get("rampUpTime").map(JavaUtils.timeStringAsSec(_)).getOrElse(0L) | ||
| if (rampUpTimeSeconds < 0) { | ||
| throw new IllegalArgumentException( | ||
| s"Invalid value '${params("rampUpTime")}'. The option 'rampUpTime' " + | ||
| "must not be negative") | ||
| } | ||
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| val numPartitions = params.get("numPartitions").map(_.toInt).getOrElse( | ||
| sqlContext.sparkContext.defaultParallelism) | ||
| if (numPartitions <= 0) { | ||
| throw new IllegalArgumentException( | ||
| s"Invalid value '${params("numPartitions")}'. The option 'numPartitions' " + | ||
| "must be positive") | ||
| } | ||
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| new RateStreamSource( | ||
| sqlContext, | ||
| metadataPath, | ||
| rowsPerSecond, | ||
| rampUpTimeSeconds, | ||
| numPartitions, | ||
| params.get("useManualClock").map(_.toBoolean).getOrElse(false) // Only for testing | ||
| ) | ||
| } | ||
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| override def createContinuousReader( | ||
| schema: Optional[StructType], | ||
| checkpointLocation: String, | ||
| options: DataSourceOptions): ContinuousReader = { | ||
| new RateStreamContinuousReader(options) | ||
| } | ||
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| override def shortName(): String = "rate" | ||
| } | ||
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| object RateSourceProvider { | ||
| val SCHEMA = | ||
| StructType(StructField("timestamp", TimestampType) :: StructField("value", LongType) :: Nil) | ||
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| val VERSION = 1 | ||
| } | ||
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| class RateStreamSource( | ||
| sqlContext: SQLContext, | ||
| metadataPath: String, | ||
| rowsPerSecond: Long, | ||
| rampUpTimeSeconds: Long, | ||
| numPartitions: Int, | ||
| useManualClock: Boolean) extends Source with Logging { | ||
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| import RateSourceProvider._ | ||
| import RateStreamSource._ | ||
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| val clock = if (useManualClock) new ManualClock else new SystemClock | ||
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| private val maxSeconds = Long.MaxValue / rowsPerSecond | ||
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| if (rampUpTimeSeconds > maxSeconds) { | ||
| throw new ArithmeticException( | ||
| s"Integer overflow. Max offset with $rowsPerSecond rowsPerSecond" + | ||
| s" is $maxSeconds, but 'rampUpTimeSeconds' is $rampUpTimeSeconds.") | ||
| } | ||
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| private val startTimeMs = { | ||
| val metadataLog = | ||
| new HDFSMetadataLog[LongOffset](sqlContext.sparkSession, metadataPath) { | ||
| override def serialize(metadata: LongOffset, out: OutputStream): Unit = { | ||
| val writer = new BufferedWriter(new OutputStreamWriter(out, StandardCharsets.UTF_8)) | ||
| writer.write("v" + VERSION + "\n") | ||
| writer.write(metadata.json) | ||
| writer.flush | ||
| } | ||
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| override def deserialize(in: InputStream): LongOffset = { | ||
| val content = IOUtils.toString(new InputStreamReader(in, StandardCharsets.UTF_8)) | ||
| // HDFSMetadataLog guarantees that it never creates a partial file. | ||
| assert(content.length != 0) | ||
| if (content(0) == 'v') { | ||
| val indexOfNewLine = content.indexOf("\n") | ||
| if (indexOfNewLine > 0) { | ||
| val version = parseVersion(content.substring(0, indexOfNewLine), VERSION) | ||
| LongOffset(SerializedOffset(content.substring(indexOfNewLine + 1))) | ||
| } else { | ||
| throw new IllegalStateException( | ||
| s"Log file was malformed: failed to detect the log file version line.") | ||
| } | ||
| } else { | ||
| throw new IllegalStateException( | ||
| s"Log file was malformed: failed to detect the log file version line.") | ||
| } | ||
| } | ||
| } | ||
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| metadataLog.get(0).getOrElse { | ||
| val offset = LongOffset(clock.getTimeMillis()) | ||
| metadataLog.add(0, offset) | ||
| logInfo(s"Start time: $offset") | ||
| offset | ||
| }.offset | ||
| } | ||
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| /** When the system time runs backward, "lastTimeMs" will make sure we are still monotonic. */ | ||
| @volatile private var lastTimeMs = startTimeMs | ||
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| override def schema: StructType = RateSourceProvider.SCHEMA | ||
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| override def getOffset: Option[Offset] = { | ||
| val now = clock.getTimeMillis() | ||
| if (lastTimeMs < now) { | ||
| lastTimeMs = now | ||
| } | ||
| Some(LongOffset(TimeUnit.MILLISECONDS.toSeconds(lastTimeMs - startTimeMs))) | ||
| } | ||
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| override def getBatch(start: Option[Offset], end: Offset): DataFrame = { | ||
| val startSeconds = start.flatMap(LongOffset.convert(_).map(_.offset)).getOrElse(0L) | ||
| val endSeconds = LongOffset.convert(end).map(_.offset).getOrElse(0L) | ||
| assert(startSeconds <= endSeconds, s"startSeconds($startSeconds) > endSeconds($endSeconds)") | ||
| if (endSeconds > maxSeconds) { | ||
| throw new ArithmeticException("Integer overflow. Max offset with " + | ||
| s"$rowsPerSecond rowsPerSecond is $maxSeconds, but it's $endSeconds now.") | ||
| } | ||
| // Fix "lastTimeMs" for recovery | ||
| if (lastTimeMs < TimeUnit.SECONDS.toMillis(endSeconds) + startTimeMs) { | ||
| lastTimeMs = TimeUnit.SECONDS.toMillis(endSeconds) + startTimeMs | ||
| } | ||
| val rangeStart = valueAtSecond(startSeconds, rowsPerSecond, rampUpTimeSeconds) | ||
| val rangeEnd = valueAtSecond(endSeconds, rowsPerSecond, rampUpTimeSeconds) | ||
| logDebug(s"startSeconds: $startSeconds, endSeconds: $endSeconds, " + | ||
| s"rangeStart: $rangeStart, rangeEnd: $rangeEnd") | ||
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| if (rangeStart == rangeEnd) { | ||
| return sqlContext.internalCreateDataFrame( | ||
| sqlContext.sparkContext.emptyRDD, schema, isStreaming = true) | ||
| } | ||
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| val localStartTimeMs = startTimeMs + TimeUnit.SECONDS.toMillis(startSeconds) | ||
| val relativeMsPerValue = | ||
| TimeUnit.SECONDS.toMillis(endSeconds - startSeconds).toDouble / (rangeEnd - rangeStart) | ||
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| val rdd = sqlContext.sparkContext.range(rangeStart, rangeEnd, 1, numPartitions).map { v => | ||
| val relative = math.round((v - rangeStart) * relativeMsPerValue) | ||
| InternalRow(DateTimeUtils.fromMillis(relative + localStartTimeMs), v) | ||
| } | ||
| sqlContext.internalCreateDataFrame(rdd, schema, isStreaming = true) | ||
| } | ||
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| override def stop(): Unit = {} | ||
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| override def toString: String = s"RateSource[rowsPerSecond=$rowsPerSecond, " + | ||
| s"rampUpTimeSeconds=$rampUpTimeSeconds, numPartitions=$numPartitions]" | ||
| } | ||
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| object RateStreamSource { | ||
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| /** Calculate the end value we will emit at the time `seconds`. */ | ||
| def valueAtSecond(seconds: Long, rowsPerSecond: Long, rampUpTimeSeconds: Long): Long = { | ||
| // E.g., rampUpTimeSeconds = 4, rowsPerSecond = 10 | ||
| // Then speedDeltaPerSecond = 2 | ||
| // | ||
| // seconds = 0 1 2 3 4 5 6 | ||
| // speed = 0 2 4 6 8 10 10 (speedDeltaPerSecond * seconds) | ||
| // end value = 0 2 6 12 20 30 40 (0 + speedDeltaPerSecond * seconds) * (seconds + 1) / 2 | ||
| val speedDeltaPerSecond = rowsPerSecond / (rampUpTimeSeconds + 1) | ||
| if (seconds <= rampUpTimeSeconds) { | ||
| // Calculate "(0 + speedDeltaPerSecond * seconds) * (seconds + 1) / 2" in a special way to | ||
| // avoid overflow | ||
| if (seconds % 2 == 1) { | ||
| (seconds + 1) / 2 * speedDeltaPerSecond * seconds | ||
| } else { | ||
| seconds / 2 * speedDeltaPerSecond * (seconds + 1) | ||
| } | ||
| } else { | ||
| // rampUpPart is just a special case of the above formula: rampUpTimeSeconds == seconds | ||
| val rampUpPart = valueAtSecond(rampUpTimeSeconds, rowsPerSecond, rampUpTimeSeconds) | ||
| rampUpPart + (seconds - rampUpTimeSeconds) * rowsPerSecond | ||
| } | ||
| } | ||
| } |
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