如何在一个Sparkcontext中从Pyspark中的独立线程运行多个作业？

Question

我在Scala和Java中几乎找不到相同的示例代码。谁能给出一个如何使用Pyspark实现这一点的例子吗？

Answer 1

我遇到了同样的问题，所以我创建了一个很小的自包含的示例。我使用Python的线程模块创建多个线程，并同时提交多个spark作业。

请注意，默认情况下，spark将以先进先出(FIFO)运行作业:http://spark.apache.org/docs/latest/job-scheduling.html#scheduling-intern-an-application。在下面的示例中，我将其更改为公平调度

# Prereqs:
# set 
# spark.dynamicAllocation.enabled         true
# spark.shuffle.service.enabled           true
  spark.scheduler.mode                    FAIR
# in spark-defaults.conf

import threading
from pyspark import SparkContext, SparkConf

def task(sc, i):
  print sc.parallelize(range(i*10000)).count()

def run_multiple_jobs():
  conf = SparkConf().setMaster('local[*]').setAppName('appname')
  # Set scheduler to FAIR: http://spark.apache.org/docs/latest/job-scheduling.html#scheduling-within-an-application
  conf.set('spark.scheduler.mode', 'FAIR')
  sc = SparkContext(conf=conf)
  for i in range(4):
    t = threading.Thread(target=task, args=(sc, i))
    t.start()
    print 'spark task', i, 'has started'


run_multiple_jobs()

输出：

spark task 0 has started
spark task 1 has started
spark task 2 has started
spark task 3 has started
30000
0 
10000
20000