当我将pyspark保存为parquet文件时,我得到了以下错误:
Py4JJavaError: An error occurred while calling o50.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.dataso
我有一个星火流+卡夫卡的例子。它在IDE中运行得很好。但是,当我尝试从控制台通过SBT编译它时,比如sbt编译。有个错误。
主修班:
val conf = new SparkConf().setMaster("local[*]").setAppName("KafkaReceiver")
val ssc = new StreamingContext(conf, Seconds(5))
val kafkaStream1 = KafkaUtils.createStream(ssc, "localhost:2181", "spark-s
我在添加spark-dependencies时遇到以下错误:
Error while importing sbt project:
OpenJDK Server VM warning: ignoring option MaxPermSize=384M; support was removed in 8.0
和
::::::::::::::::::::::::::::::::::::::::::::::
[warn] :: UNRESOLVED DEPENDENCIES ::
[warn] :::::::::::::::::::::::::::::::::
所以我创建了一个调用Python脚本并执行PySpark转换的作业。然而,当我从AWS Cloudwatch查看Output时,输出中有许多对我来说并不重要的信息。例如: at org.apache.spark.rdd.NewHadoopRDD$$anon$1.liftedTree1$1(NewHadoopRDD.scala:199)
at org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:196)
at org.apache.spark.rdd.NewHadoopRDD.compute(New
正在尝试在Spark2中运行JavaSparkSQLExample。使用spark-core_2.11-2.0.2和spark-sql_2.11-2.0.2。有一个错误:The method createGlobalTempView(String) is undefined for the type Dataset<Row>.
实际上,并没有定义这个方法。有这个功能。任何人都有这方面的线索。
另外,我们如何构建会话--因为您不能使用:.config("spark.some.config.option", "some-value")运行。
SparkC
我尝试在databricks中运行以下代码,以便调用spark会话并使用它打开csv文件:
spark
fireServiceCallsDF = spark.read.csv('/mnt/sf_open_data/fire_dept_calls_for_service/Fire_Department_Calls_for_Service.csv', header=True, inferSchema=True)
我得到了以下错误:
NameError:name 'spark' is not defined
你知道可能出了什么问题吗?
我还试着运行:
from py
我正在读取一个目录的文本文件从我的本地机器在火花。当我使用星火提交运行它时,我将得到以下异常
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
17/03/30 01:15:22 INFO SparkContext: Running Spark version 2.1.0
17/03/30 01:15:23 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using
I am trying to read a csv (native) file from an S3 bucket using a locally running Spark - Scala. I am able to read the file using the http protocol but I intend to use the s3a protocol.
Below is the configuration setup before the call
spark.sparkContext.hadoopConfiguration.set("fs.s3a.impl",
我尝试使用sc.parallelize创建RDD。它给出了一个例外,因为:
Exception in thread "main" java.lang.ExceptionInInitializerError
at org.apache.spark.SparkContext.withScope(SparkContext.scala:701)
at org.apache.spark.SparkContext.parallelize(SparkContext.scala:718)
at df_avro.SampleDf$.main(SampleDf.sca