【发布时间】:2019-04-21 05:36:25
【问题描述】:
我建立了一个带有生产者和消费者的 kafka 系统,将 json 文件的行作为消息流式传输。
使用 pyspark,我需要分析不同流窗口的数据。为此,我需要查看 pyspark 流式传输的数据......我该怎么做?
为了运行我使用Yannael's Docker 容器的代码。这是我的python代码:
# Add dependencies and load modules
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--conf spark.ui.port=4040 --packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.0.0,com.datastax.spark:spark-cassandra-connector_2.11:2.0.0-M3 pyspark-shell'
from kafka import KafkaConsumer
from random import randint
from time import sleep
# Load modules and start SparkContext
from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext, Row
conf = SparkConf() \
.setAppName("Streaming test") \
.setMaster("local[2]") \
.set("spark.cassandra.connection.host", "127.0.0.1")
try:
sc.stop()
except:
pass
sc = SparkContext(conf=conf)
sqlContext=SQLContext(sc)
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
# Create streaming task
ssc = StreamingContext(sc, 0.60)
kafkaStream = KafkaUtils.createStream(ssc, "127.0.0.1:2181", "spark-streaming-consumer", {'test': 1})
ssc.start()
【问题讨论】:
标签: python apache-spark pyspark apache-kafka