Spark源码研读-散篇记录:Spark内置RPC框架之TransportConf

Posted

tags:

篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Spark源码研读-散篇记录:Spark内置RPC框架之TransportConf相关的知识,希望对你有一定的参考价值。

1 Spark版本

Spark 2.1.0。

2 说明

去年在网易之初,已经开发了一个完整的RPC框架,其中使用的核心技术也是Netty,所以当看到Spark的RPC框架时,并不觉得太陌生,关于个人开发的这个RPC框架,真正完全可用是在今年,明年会完善一下,开源出来,因为个人觉得弄得一个简单RPC框架的技术原理,对于大数据、分布式计算相关的知识,真的是帮助太大。
本篇说一下TransportContext、TransportConf、ConfigProvider、SparkTransportConf,也是仅仅作为个人的阅读记录。
TransportContext是创建RPC server和client的关键类,其中需要使用到的配置信息保存在TransportConf对象,TransportConf对象用于存储核心配置信息的对象为ConfigProvider,在实际使用中,一般使用SparkTransportConf来创建TransportConf对象,可以说,SparkTransportConf通过ConfigProvider对象将SparkConf和TransportConf连接了起来,所以实际上,在TransportConf对象中,是可以读取到SparkConf的配置信息的。

3 源码

依然是在关键地方加了个人的注释,有些地方英文注释本身已经说得很明白了,就不加注释了。

3.1 TransportConf

/*
 * 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.network.util;

import com.google.common.primitives.Ints;

/**
 * A central location that tracks all the settings we expose to users.
 */
public class TransportConf {

  static {
    // Set this due to Netty PR #5661 for Netty 4.0.37+ to work
    System.setProperty("io.netty.maxDirectMemory", "0");
  }

  private final String SPARK_NETWORK_IO_MODE_KEY;
  private final String SPARK_NETWORK_IO_PREFERDIRECTBUFS_KEY;
  private final String SPARK_NETWORK_IO_CONNECTIONTIMEOUT_KEY;
  private final String SPARK_NETWORK_IO_BACKLOG_KEY;
  private final String SPARK_NETWORK_IO_NUMCONNECTIONSPERPEER_KEY;
  private final String SPARK_NETWORK_IO_SERVERTHREADS_KEY;
  private final String SPARK_NETWORK_IO_CLIENTTHREADS_KEY;
  private final String SPARK_NETWORK_IO_RECEIVEBUFFER_KEY;
  private final String SPARK_NETWORK_IO_SENDBUFFER_KEY;
  private final String SPARK_NETWORK_SASL_TIMEOUT_KEY;
  private final String SPARK_NETWORK_IO_MAXRETRIES_KEY;
  private final String SPARK_NETWORK_IO_RETRYWAIT_KEY;
  private final String SPARK_NETWORK_IO_LAZYFD_KEY;

  private final ConfigProvider conf;  // 配置提供者

  private final String module;        // 配置的模块名称

  public TransportConf(String module, ConfigProvider conf) {
    this.module = module;
    this.conf = conf;
    SPARK_NETWORK_IO_MODE_KEY = getConfKey("io.mode");
    SPARK_NETWORK_IO_PREFERDIRECTBUFS_KEY = getConfKey("io.preferDirectBufs");
    SPARK_NETWORK_IO_CONNECTIONTIMEOUT_KEY = getConfKey("io.connectionTimeout");
    SPARK_NETWORK_IO_BACKLOG_KEY = getConfKey("io.backLog");
    SPARK_NETWORK_IO_NUMCONNECTIONSPERPEER_KEY =  getConfKey("io.numConnectionsPerPeer");
    SPARK_NETWORK_IO_SERVERTHREADS_KEY = getConfKey("io.serverThreads");
    SPARK_NETWORK_IO_CLIENTTHREADS_KEY = getConfKey("io.clientThreads");
    SPARK_NETWORK_IO_RECEIVEBUFFER_KEY = getConfKey("io.receiveBuffer");
    SPARK_NETWORK_IO_SENDBUFFER_KEY = getConfKey("io.sendBuffer");
    SPARK_NETWORK_SASL_TIMEOUT_KEY = getConfKey("sasl.timeout");
    SPARK_NETWORK_IO_MAXRETRIES_KEY = getConfKey("io.maxRetries");
    SPARK_NETWORK_IO_RETRYWAIT_KEY = getConfKey("io.retryWait");
    SPARK_NETWORK_IO_LAZYFD_KEY = getConfKey("io.lazyFD");
  }

  public int getInt(String name, int defaultValue) {
    return conf.getInt(name, defaultValue);
  }

  private String getConfKey(String suffix) {
    return "spark." + module + "." + suffix;
  }

  /** IO mode: nio or epoll */
  public String ioMode() { return conf.get(SPARK_NETWORK_IO_MODE_KEY, "NIO").toUpperCase(); }

  /** If true, we will prefer allocating off-heap byte buffers within Netty. */
  public boolean preferDirectBufs() {
    return conf.getBoolean(SPARK_NETWORK_IO_PREFERDIRECTBUFS_KEY, true);
  }

  /** Connect timeout in milliseconds. Default 120 secs. */
  public int connectionTimeoutMs() {
    long defaultNetworkTimeoutS = JavaUtils.timeStringAsSec(
      conf.get("spark.network.timeout", "120s"));
    long defaultTimeoutMs = JavaUtils.timeStringAsSec(
      conf.get(SPARK_NETWORK_IO_CONNECTIONTIMEOUT_KEY, defaultNetworkTimeoutS + "s")) * 1000;
    return (int) defaultTimeoutMs;
  }

  /** Number of concurrent connections between two nodes for fetching data. */
  public int numConnectionsPerPeer() {
    return conf.getInt(SPARK_NETWORK_IO_NUMCONNECTIONSPERPEER_KEY, 1);
  }

  /** Requested maximum length of the queue of incoming connections. Default -1 for no backlog. */
  public int backLog() { return conf.getInt(SPARK_NETWORK_IO_BACKLOG_KEY, -1); }

  /** Number of threads used in the server thread pool. Default to 0, which is 2x#cores. */
  public int serverThreads() { return conf.getInt(SPARK_NETWORK_IO_SERVERTHREADS_KEY, 0); }

  /** Number of threads used in the client thread pool. Default to 0, which is 2x#cores. */
  public int clientThreads() { return conf.getInt(SPARK_NETWORK_IO_CLIENTTHREADS_KEY, 0); }

  /**
   * Receive buffer size (SO_RCVBUF).
   * Note: the optimal size for receive buffer and send buffer should be
   *  latency * network_bandwidth.
   * Assuming latency = 1ms, network_bandwidth = 10Gbps
   *  buffer size should be ~ 1.25MB
   */
  public int receiveBuf() { return conf.getInt(SPARK_NETWORK_IO_RECEIVEBUFFER_KEY, -1); }

  /** Send buffer size (SO_SNDBUF). */
  public int sendBuf() { return conf.getInt(SPARK_NETWORK_IO_SENDBUFFER_KEY, -1); }

  /** Timeout for a single round trip of SASL token exchange, in milliseconds. */
  public int saslRTTimeoutMs() {
    return (int) JavaUtils.timeStringAsSec(conf.get(SPARK_NETWORK_SASL_TIMEOUT_KEY, "30s")) * 1000;
  }

  /**
   * Max number of times we will try IO exceptions (such as connection timeouts) per request.
   * If set to 0, we will not do any retries.
   */
  public int maxIORetries() { return conf.getInt(SPARK_NETWORK_IO_MAXRETRIES_KEY, 3); }

  /**
   * Time (in milliseconds) that we will wait in order to perform a retry after an IOException.
   * Only relevant if maxIORetries > 0.
   */
  public int ioRetryWaitTimeMs() {
    return (int) JavaUtils.timeStringAsSec(conf.get(SPARK_NETWORK_IO_RETRYWAIT_KEY, "5s")) * 1000;
  }

  /**
   * Minimum size of a block that we should start using memory map rather than reading in through
   * normal IO operations. This prevents Spark from memory mapping very small blocks. In general,
   * memory mapping has high overhead for blocks close to or below the page size of the OS.
   */
  public int memoryMapBytes() {
    return Ints.checkedCast(JavaUtils.byteStringAsBytes(
      conf.get("spark.storage.memoryMapThreshold", "2m")));
  }

  /**
   * Whether to initialize FileDescriptor lazily or not. If true, file descriptors are
   * created only when data is going to be transferred. This can reduce the number of open files.
   */
  public boolean lazyFileDescriptor() {
    return conf.getBoolean(SPARK_NETWORK_IO_LAZYFD_KEY, true);
  }

  /**
   * Maximum number of retries when binding to a port before giving up.
   */
  public int portMaxRetries() {
    return conf.getInt("spark.port.maxRetries", 16);
  }

  /**
   * Maximum number of bytes to be encrypted at a time when SASL encryption is enabled.
   */
  public int maxSaslEncryptedBlockSize() {
    return Ints.checkedCast(JavaUtils.byteStringAsBytes(
      conf.get("spark.network.sasl.maxEncryptedBlockSize", "64k")));
  }

  /**
   * Whether the server should enforce encryption on SASL-authenticated connections.
   */
  public boolean saslServerAlwaysEncrypt() {
    return conf.getBoolean("spark.network.sasl.serverAlwaysEncrypt", false);
  }

}

3.2 ConfigProvider

/*
 * 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.network.util;

import java.util.NoSuchElementException;

/**
 * Provides a mechanism for constructing a {@link TransportConf} using some sort of configuration.
 * Leaf Note:
 * 提供一种使用某些配置的方式去构造一个TransportConf对象,其实什么意思呢?
 * 看到其提供了抽象get方法,该类中所有非抽象方法最终都是调用该抽象方法的,所以显然在构造ConfigProvider对象时,
 * 就可以重载get(String name)方法,如何重载?它的返回值使用SparkConf的get()方法fuc获取SparkConf对象的配置
 * 信息就可以了,查看SparkTransportConf,正是这样来使用ConfigProvider的
 */
public abstract class ConfigProvider {
  /** Obtains the value of the given config, throws NoSuchElementException if it doesn‘t exist. */
  public abstract String get(String name);

  public String get(String name, String defaultValue) {
    try {
      return get(name);
    } catch (NoSuchElementException e) {
      return defaultValue;
    }
  }

  public int getInt(String name, int defaultValue) {
    return Integer.parseInt(get(name, Integer.toString(defaultValue)));
  }

  public long getLong(String name, long defaultValue) {
    return Long.parseLong(get(name, Long.toString(defaultValue)));
  }

  public double getDouble(String name, double defaultValue) {
    return Double.parseDouble(get(name, Double.toString(defaultValue)));
  }

  public boolean getBoolean(String name, boolean defaultValue) {
    return Boolean.parseBoolean(get(name, Boolean.toString(defaultValue)));
  }
}

3.3 SparkTransportConf

/*
 * 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.network.netty

import org.apache.spark.SparkConf
import org.apache.spark.network.util.{ConfigProvider, TransportConf}

/**
 * Provides a utility for transforming from a SparkConf inside a Spark JVM (e.g., Executor,
 * Driver, or a standalone shuffle service) into a TransportConf with details on our environment
 * like the number of cores that are allocated to this JVM.
  * Leaf Note:
  * 一般创建TransportConf是通过SparkTransportConf来进行创建的,
  * SparkTransportConf一个很重要的作用是,将SparkConf与TransportConf连接起来,那怎么做到的?
  * 那就是使用SparkConf的get方法去代理实现ConfigProvider的抽象get方法,而恰恰TransportConf
  * 中有一个ConfigProvider的属性
 */
object SparkTransportConf {
  /**
   * Specifies an upper bound on the number of Netty threads that Spark requires by default.
   * In practice, only 2-4 cores should be required to transfer roughly 10 Gb/s, and each core
   * that we use will have an initial overhead of roughly 32 MB of off-heap memory, which comes
   * at a premium.
   *
   * Thus, this value should still retain maximum throughput and reduce wasted off-heap memory
   * allocation. It can be overridden by setting the number of serverThreads and clientThreads
   * manually in Spark‘s configuration.
   */
  private val MAX_DEFAULT_NETTY_THREADS = 8

  /**
   * Utility for creating a [[TransportConf]] from a [[SparkConf]].
   * @param _conf the [[SparkConf]]
   * @param module the module name
   * @param numUsableCores if nonzero, this will restrict the server and client threads to only
   *                       use the given number of cores, rather than all of the machine‘s cores.
   *                       This restriction will only occur if these properties are not already set.
   */
  def fromSparkConf(_conf: SparkConf, module: String, numUsableCores: Int = 0): TransportConf = {
    val conf = _conf.clone

    // Specify thread configuration based on our JVM‘s allocation of cores (rather than necessarily
    // assuming we have all the machine‘s cores).
    // NB: Only set if serverThreads/clientThreads not already set.
    val numThreads = defaultNumThreads(numUsableCores)
    conf.setIfMissing(s"spark.$module.io.serverThreads", numThreads.toString)
    conf.setIfMissing(s"spark.$module.io.clientThreads", numThreads.toString)

    new TransportConf(module, new ConfigProvider {
      override def get(name: String): String = conf.get(name)
    })
  }

  /**
   * Returns the default number of threads for both the Netty client and server thread pools.
   * If numUsableCores is 0, we will use Runtime get an approximate number of available cores.
   */
  private def defaultNumThreads(numUsableCores: Int): Int = {
    val availableCores =
      if (numUsableCores > 0) numUsableCores else Runtime.getRuntime.availableProcessors()
    math.min(availableCores, MAX_DEFAULT_NETTY_THREADS)
  }
}

以上是关于Spark源码研读-散篇记录:Spark内置RPC框架之TransportConf的主要内容,如果未能解决你的问题,请参考以下文章

搭建Spark源码研读和代码调试的开发环境

阅读源码|Spark 与 Flink 的 RPC 实现

Spark RPC 框架源码分析运行时序

Spark 1.6 RPC内幕解密:运行机制源码详解Netty与Akka等(DT大数据梦工厂)

Spark RPC使用记录(spark-2.2.0)

spark源码解析总结