将数据从pyspark写入ElasticSearch
我跟随本文将一些数据发送到AWS ES,并使用了jar elasticsearch-hadoop。这是我的脚本:
from pyspark import SparkContext, SparkConffrom pyspark.sql import SQLContext
if __name__ == "__main__":
conf = SparkConf().setAppName("WriteToES")
sc = SparkContext(conf=conf)
sqlContext = SQLContext(sc)
es_conf = {"es.nodes" : "https://search-elasticsearchdomaine.region.es.amazonaws.com/",
"es.port" : "9200","es.nodes.client.only" : "true","es.resource" : "sensor_counts/metrics"}
es_df_p = sqlContext.read.format("com.databricks.spark.csv").option("header", "true").load("output/part-00000-c353bb29-f189-4189-b35b-f7f1af717355.csv")
es_df_pf= es_df_p.groupBy("network_key")
es_df_pf.saveAsNewAPIHadoopFile(
path='-',
outputFormatClass="org.elasticsearch.hadoop.mr.EsOutputFormat",
keyClass="org.apache.hadoop.io.NullWritable",
valueClass="org.elasticsearch.hadoop.mr.LinkedMapWritable",
conf=es_conf)
然后运行以下命令行:
spark-submit --jars elasticsearch-spark-20_2.11-5.3.1.jar write_to_es.py
其中write_to_es.py是上面的脚本。
这是我得到的错误:
17/05/05 17:51:52 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)17/05/05 17:51:52 INFO HadoopRDD: Input split: file:/home/user/spark-2.1.0-bin-hadoop2.7/output/part-00000-c353bb29-f189-4189-b35b-f7f1af717355.csv:0+178633
17/05/05 17:51:52 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1143 bytes result sent to driver
17/05/05 17:51:52 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 11 ms on localhost (executor driver) (1/1)
17/05/05 17:51:52 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool
17/05/05 17:51:52 INFO DAGScheduler: ResultStage 1 (load at NativeMethodAccessorImpl.java:0) finished in 0,011 s
17/05/05 17:51:52 INFO DAGScheduler: Job 1 finished: load at NativeMethodAccessorImpl.java:0, took 0,018727 s
17/05/05 17:51:52 INFO BlockManagerInfo: Removed broadcast_1_piece0 on 192.168.1.26:39609 in memory (size: 2.1 KB, free: 366.3 MB)
17/05/05 17:51:52 INFO BlockManagerInfo: Removed broadcast_2_piece0 on 192.168.1.26:39609 in memory (size: 22.9 KB, free: 366.3 MB)
17/05/05 17:51:52 INFO BlockManagerInfo: Removed broadcast_3_piece0 on 192.168.1.26:39609 in memory (size: 2.1 KB, free: 366.3 MB)
Traceback (most recent call last):
File "/home/user/spark-2.1.0-bin-hadoop2.7/write_to_es.py", line 11, in <module>
es_df_pf.saveAsNewAPIHadoopFile(
File "/home/user/spark-2.1.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/sql/dataframe.py", line 964, in __getattr__
AttributeError: 'DataFrame' object has no attribute 'saveAsNewAPIHadoopFile'
17/05/05 17:51:53 INFO SparkContext: Invoking stop() from shutdown hook
17/05/05 17:51:53 INFO SparkUI: Stopped Spark web UI at http://192.168.1.26:4040
17/05/05 17:51:53 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/05/05 17:51:53 INFO MemoryStore: MemoryStore cleared
17/05/05 17:51:53 INFO BlockManager: BlockManager stopped
17/05/05 17:51:53 INFO BlockManagerMaster: BlockManagerMaster stopped
17/05/05 17:51:53 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/05/05 17:51:53 INFO SparkContext: Successfully stopped SparkContext
17/05/05 17:51:53 INFO ShutdownHookManager: Shutdown hook called
17/05/05 17:51:53 INFO ShutdownHookManager: Deleting directory /tmp/spark-501c4efa-5402-430e-93c1-aaff4caddef0
17/05/05 17:51:53 INFO ShutdownHookManager: Deleting directory /tmp/spark-501c4efa-5402-430e-93c1-aaff4caddef0/pyspark-52406fa8-e8d1-4aca-bcb6-91748dc87507
如何解决这个问题:
AttributeError: 'DataFrame' object has no attribute 'saveAsNewAPIHadoopFile'
任何帮助或建议,我们将不胜感激。
回答:
我有同样的问题。
看完这篇文章,我找到了答案!!!
您必须PythonRDD
像这样转换为Type:
>>> type(df)<class 'pyspark.sql.dataframe.DataFrame'>
>>> type(df.rdd)
<class 'pyspark.rdd.RDD'>
>>> df.rdd.saveAsNewAPIHadoopFile(...) # Got the same error message
>>> df.printSchema() # My schema
root
|-- id: string (nullable = true)
...
# Let's convert to PythonRDD
>>> python_rdd = df.map(lambda item: ('key', {
... 'id': item['id'],
...
... }))
>>> python_rdd
PythonRDD[42] at RDD at PythonRDD.scala:43
>>> python_rdd.saveAsNewAPIHadoopFile(...) # Now, success
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