一个根据所给资源自动配置CDH中Hadoop等参数的工具

Python的名字为：cdh_auto_configuration.py，完整内容如下：

#!/usr/bin/env python
'''
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.
'''

import optparse
from pprint import pprint
import logging
import sys
import math
import ast

''' Reserved for OS + DN + NM,  Map: Memory => Reservation '''
reservedStack = { 4:1, 8:2, 16:2, 24:4, 48:6, 64:8, 72:8, 96:12,
                   128:24, 256:32, 512:64}
''' Reserved for HBase. Map: Memory => Reservation '''
 
reservedHBase = {4:1, 8:1, 16:2, 24:4, 48:8, 64:8, 72:8, 96:16,
                   128:24, 256:32, 512:64}
GB = 1024

def getMinContainerSize(memory):
  if (memory <= 4):
    return 256
  elif (memory <= 8):
    return 512
  elif (memory <= 24):
    return 1024
  else:
    return 2048
  pass

def getReservedStackMemory(memory):
  if (reservedStack.has_key(memory)):
    return reservedStack[memory]
  if (memory <= 4):
    ret = 1
  elif (memory >= 512):
    ret = 64
  else:
    ret = 1
  return ret

def getReservedHBaseMem(memory):
  if (reservedHBase.has_key(memory)):
    return reservedHBase[memory]
  if (memory <= 4):
    ret = 1
  elif (memory >= 512):
    ret = 64
  else:
    ret = 2
  return ret
                    
def getRoundedMemory(memory):
  denominator = 128
  if (memory > 4096):
    denominator = 1024
  elif (memory > 2048):
    denominator = 512
  elif (memory > 1024):
    denominator = 256
  else:
    denominator = 128

  return int(math.floor(memory/denominator)) * denominator

def main():
  log = logging.getLogger(__name__)
  out_hdlr = logging.StreamHandler(sys.stdout)
  out_hdlr.setFormatter(logging.Formatter(' %(message)s'))
  out_hdlr.setLevel(logging.INFO)
  log.addHandler(out_hdlr)
  log.setLevel(logging.INFO)
  parser = optparse.OptionParser()
  memory = 0
  cores = 0
  disks = 0
  hbaseEnabled = True
  parser.add_option('-c', '--cores', default = 16,
                     help = 'Number of cores on each host')
  parser.add_option('-m', '--memory', default = 64,
                    help = 'Amount of Memory on each host in GB')
  parser.add_option('-d', '--disks', default = 4,
                    help = 'Number of disks on each host')
  parser.add_option('-k', '--hbase', default = "True",
                    help = 'True if HBase is installed, False is not')
  (options, args) = parser.parse_args()
 
  cores = int (options.cores)
  memory = int (options.memory)
  disks = int (options.disks)
  hbaseEnabled = ast.literal_eval(options.hbase)
 
  log.info("Using cores=" +  str(cores) + " memory=" + str(memory) + "GB" +
            " disks=" + str(disks) + " hbase=" + str(hbaseEnabled))
  minContainerSize = getMinContainerSize(memory)
  reservedStackMemory = getReservedStackMemory(memory)
  reservedHBaseMemory = 0
  if (hbaseEnabled):
    reservedHBaseMemory = getReservedHBaseMem(memory)
  reservedMem = reservedStackMemory + reservedHBaseMemory
  usableMem = memory - reservedMem
  memory -= (reservedMem)
  if (memory < 2):
    memory = 2
    reservedMem = max(0, memory - reservedMem)
    
  memory *= GB
 
  containers = int (max(3, min(2 * cores,
                         min(math.ceil(1.8 * float(disks)),
                              memory/minContainerSize))))
  log.info("Profile: cores=" + str(cores) + " memory=" + str(memory) + "MB"
           + " reserved=" + str(reservedMem) + "GB" + " usableMem="
           + str(usableMem) + "GB" + " disks=" + str(disks))

  container_ram =  getRoundedMemory(abs(memory/containers))
  log.info("Num Container=" + str(containers))
  log.info("Container Ram=" + str(container_ram) + "MB")
  log.info("Used Ram=" + str(int (containers*container_ram/float(GB))) + "GB")
  log.info("Unused Ram=" + str(reservedMem) + "GB")
 
  ''' YARN Configs '''
  log.info("yarn.scheduler.minimum-allocation-mb=" + str(container_ram))
  log.info("yarn.scheduler.maximum-allocation-mb=" + str(containers*container_ram))
  log.info("yarn.nodemanager.resource.memory-mb=" + str(containers*container_ram))

  ''' MapReduce Configs '''
  map_memory = container_ram
  reduce_memory = container_ram
  if (container_ram < 2048):
    reduce_memory = 2 * container_ram
  am_memory = min(map_memory, reduce_memory)
  log.info("mapreduce.map.memory.mb=" + str(int(map_memory)))
  log.info("mapreduce.map.java.opts=-Xmx" + str(getRoundedMemory(int(0.8 * map_memory))) +"m")
  log.info("mapreduce.reduce.memory.mb=" + str(int(reduce_memory)))
  log.info("mapreduce.reduce.java.opts=-Xmx" + str(getRoundedMemory(int(0.8 * reduce_memory))) + "m")
  log.info("yarn.app.mapreduce.am.resource.mb=" + str(int(am_memory)))
  log.info("yarn.app.mapreduce.am.command-opts=-Xmx" + str(getRoundedMemory(int(0.8*am_memory))) + "m")
  ''' io.sort.mb cannot be greater than 2047 '''
  log.info("mapreduce.task.io.sort.mb=" + str(getRoundedMemory(int(min(0.4 * map_memory, 2047)))))

  ''' Tez Configs '''
  am_memory = max(map_memory, reduce_memory)
  log.info("tez.am.resource.memory.mb=" + str(int(am_memory)))
  log.info("tez.am.java.opts=-Xmx" + str(getRoundedMemory(int(0.8*am_memory))) + "m")
  heap_size = getRoundedMemory(int(0.8 * container_ram))
  log.info("hive.tez.container.size=" + str(int(container_ram)))
  log.info("hive.tez.java.opts=-Xmx" + str(heap_size) +"m")

  ''' Hive Configs '''
  hive_noconditional_task_size = int (getRoundedMemory(int(heap_size*0.33)) * 1024 * 1024)
  log.info("hive.auto.convert.join.noconditionaltask.size=" + str(hive_noconditional_task_size / 1000 * 1000))

  pass

if __name__ == '__main__':
  try:
    main()
  except(KeyboardInterrupt, EOFError):
    print("\nAborting ... Keyboard Interrupt.")
    sys.exit(1)

下面我们来看一下这个脚本的常用参数：

执行帮助命令：

python cdh_auto_configuration.py -h

返回结果：

Usage: cdh_auto_configuration.py [options]

Options:

  -h, --help            show this help message and exit

  -c CORES, --cores=CORES

                        Number of cores on each host

  -m MEMORY, --memory=MEMORY

                        Amount of Memory on each host in GB

  -d DISKS, --disks=DISKS

                        Number of disks on each host

  -k HBASE, --hbase=HBASE

                        True if HBase is installed, False is not

根据参数提示，下面我们来演示一下脚本的执行情况：                        
python cdh_auto_configuration.py -c 64 -m 128 -d 4 -k True

返回结果：

 Using cores=64 memory=128GB disks=4 hbase=True

 Profile: cores=64 memory=81920MB reserved=48GB usableMem=80GB disks=4

 Num Container=8

 Container Ram=10240MB

 Used Ram=80GB

 Unused Ram=48GB

 ***** mapred-site.xml *****

 mapreduce.map.memory.mb=10240

 mapreduce.map.java.opts=-Xmx8192m

 mapreduce.reduce.memory.mb=10240

 mapreduce.reduce.java.opts=-Xmx8192m

 mapreduce.task.io.sort.mb=1792

 ***** yarn-site.xml *****

 yarn.scheduler.minimum-allocation-mb=10240

 yarn.scheduler.maximum-allocation-mb=81920

 yarn.nodemanager.resource.memory-mb=81920

 yarn.app.mapreduce.am.resource.mb=10240

 yarn.app.mapreduce.am.command-opts=-Xmx8192m

 ***** tez-site.xml *****

 tez.am.resource.memory.mb=10240

 tez.am.java.opts=-Xmx8192m

 ***** hive-site.xml *****

 hive.tez.container.size=10240

 hive.tez.java.opts=-Xmx8192m
 hive.auto.convert.join.noconditionaltask.size=2684354000

然后根据实际情况进行查看分析，如果不满足你的要求，可以对上面的Python源码进行修改并重新生成配置。