5

所以我有一些数据在 Kafka 主题中进行流式传输，我正在获取这些流式数据并将其放入DataFrame. 我想在 DataFrame 中显示数据：

import os
from kafka import KafkaProducer
from pyspark.sql import SparkSession, DataFrame
import time
from datetime import datetime, timedelta

os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.2.0,org.apache.spark:spark-streaming-kafka-0-8_2.11:2.2.0 pyspark-shell'

topic_name = "my-topic"
kafka_broker = "localhost:9092"

producer = KafkaProducer(bootstrap_servers = kafka_broker)
spark = SparkSession.builder.getOrCreate()
terminate = datetime.now() + timedelta(seconds=30)

while datetime.now() < terminate:
    producer.send(topic = topic_name, value = str(datetime.now()).encode('utf-8'))
    time.sleep(1)

readDF = spark \
    .readStream \
    .format("kafka") \
    .option("kafka.bootstrap.servers", kafka_broker) \
    .option("subscribe", topic_name) \
    .load()
readDF = readDF.selectExpr("CAST(key AS STRING)","CAST(value AS STRING)")

readDF.writeStream.format("console").start()
readDF.show()

producer.close()

但是我不断收到此错误：

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/spark/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/home/spark/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o30.showString.
: org.apache.spark.sql.AnalysisException: Queries with streaming sources must be executed with writeStream.start();;
kafka
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.org$apache$spark$sql$catalyst$analysis$UnsupportedOperationChecker$$throwError(UnsupportedOperationChecker.scala:297)
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:36)
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:34)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
...
Traceback (most recent call last):
      File "test2.py", line 30, in <module>
        readDF.show()
      File "/home/spark/spark/python/pyspark/sql/dataframe.py", line 336, in show
        print(self._jdf.showString(n, 20))
      File "/home/spark/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
      File "/home/spark/spark/python/pyspark/sql/utils.py", line 69, in deco
        raise AnalysisException(s.split(': ', 1)[1], stackTrace)
    pyspark.sql.utils.AnalysisException: 'Queries with streaming sources must be executed with writeStream.start();;\nkafka'

我不明白为什么会发生异常，我writeStream.start()之前就打电话了show()。我试图摆脱，selectExpr()但这没有任何区别。有谁知道如何显示流来源的 DataFrame？我正在使用 Python 3.6.1、Kafka 0.10.2.1 和 Spark 2.2.0

4

2 回答 2

10

Streaming DataFrame 不支持该show()方法。当您调用start()方法时，它将启动一个后台线程将输入数据流式传输到接收器，并且由于您使用的是 ConsoleSink，它会将数据输出到控制台。你不需要打电话show()。

之后移除readDF.show()并添加一个睡眠，然后您应该可以在控制台中看到数据，例如

query = readDF.writeStream.format("console").start()
import time
time.sleep(10) # sleep 10 seconds
query.stop()

您还需要设置startingOffsets为earliest，否则，Kafka 源将仅从最新的偏移量开始，并且在您的情况下不会获取任何内容。

readDF = spark \
    .readStream \
    .format("kafka") \
    .option("kafka.bootstrap.servers", kafka_broker) \
    .option("startingOffsets", "earliest") \
    .option("subscribe", topic_name) \
    .load()
于 2017-07-13T23:43:10.177 回答
0

Streaming DataFrame 不直接支持 show() 方法，但是有一种方法可以通过让后台线程休眠一段时间并在内存接收器中创建的临时表上使用 show() 函数来查看数据。我可以帮助使用 show() 方法的 pyspark 方式。

在这里参考我的回答

于 2020-06-02T21:35:35.810 回答