Github user brkyvz commented on a diff in the pull request: https://github.com/apache/spark/pull/18199#discussion_r120197044 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/RateSourceProvider.scala --- @@ -0,0 +1,208 @@ +/* + * 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. + */ + +package org.apache.spark.sql.execution.streaming + +import java.io._ +import java.nio.charset.StandardCharsets +import java.util.concurrent.TimeUnit + +import org.apache.commons.io.IOUtils + +import org.apache.spark.internal.Logging +import org.apache.spark.sql.{DataFrame, SQLContext} +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.util.{CaseInsensitiveMap, DateTimeUtils} +import org.apache.spark.sql.sources.{DataSourceRegister, StreamSourceProvider} +import org.apache.spark.sql.types._ +import org.apache.spark.util.{ManualClock, SystemClock} + +/** + * 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: + * - `tuplesPerSecond` (default: 1): How many tuples should be generated per second. + * - `rampUpTimeSeconds` (default: 0): How many seconds to ramp up before the generating speed + * becomes `tuplesPerSecond`. + * - `numPartitions` (default: Spark's default parallelism): The partition number for the generated + * tuples. + */ +class RateSourceProvider extends StreamSourceProvider with DataSourceRegister { + + override def sourceSchema( + sqlContext: SQLContext, + schema: Option[StructType], + providerName: String, + parameters: Map[String, String]): (String, StructType) = + (shortName(), RateSourceProvider.SCHEMA) + + override def createSource( + sqlContext: SQLContext, + metadataPath: String, + schema: Option[StructType], + providerName: String, + parameters: Map[String, String]): Source = { + val params = CaseInsensitiveMap(parameters) + + val tuplesPerSecond = params.get("tuplesPerSecond").map(_.toLong).getOrElse(1L) + if (tuplesPerSecond <= 0) { + throw new IllegalArgumentException( + s"Invalid value '${params("tuplesPerSecond")}' for option 'tuplesPerSecond', " + + "must be positive") + } + + val rampUpTimeSeconds = params.get("rampUpTimeSeconds").map(_.toLong).getOrElse(0L) + if (rampUpTimeSeconds < 0) { + throw new IllegalArgumentException( + s"Invalid value '${params("rampUpTimeSeconds")}' for option 'rampUpTimeSeconds', " + + "must not be negative") + } + + val numPartitions = params.get("numPartitions").map(_.toInt).getOrElse( + sqlContext.sparkContext.defaultParallelism) + if (numPartitions <= 0) { + throw new IllegalArgumentException( + s"Invalid value '${params("numPartitions")}' for option 'numPartitions', " + + "must be positive") + } + + new RateStreamSource( + sqlContext, + metadataPath, + tuplesPerSecond, + rampUpTimeSeconds, + numPartitions, + params.get("useManualClock").map(_.toBoolean).getOrElse(false) // Only for testing + ) + } + override def shortName(): String = "rate" +} + +object RateSourceProvider { + val SCHEMA = + StructType(StructField("timestamp", TimestampType) :: StructField("value", LongType) :: Nil) + + val VERSION = 1 +} + +class RateStreamSource( + sqlContext: SQLContext, + metadataPath: String, + tuplesPerSecond: Long, + rampUpTimeSeconds: Long, + numPartitions: Int, + useManualClock: Boolean) extends Source with Logging { + + import RateSourceProvider._ + + val clock = if (useManualClock) new ManualClock else new SystemClock + + private val maxSeconds = Long.MaxValue / tuplesPerSecond + + if (rampUpTimeSeconds > maxSeconds) { + throw new ArithmeticException("integer overflow. Max offset with tuplesPerSecond " + --- End diff -- nit: `Integer` also may be better to write `$tuplesPerSecond tuplesPerSecond` instead of `tuplesPerSecond $tuplesPerSecond`.
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