Я пытаюсь загрузить файл в spark с помощью pyspark, я получаю эту ошибку, не могу понять, проблема возникает при нажатии на команду ниже, пытаясь загрузить файл CSV, который в моем локальном домекаталог.
Я использую режим кластера искр, а не локальный режим.Но проблема возникает для обоих режимов.
df_Csv = (spark.read.format("csv")
.option("header", "true")
.option("mode", "DROPMALFORMED")
.load("file://"+csv_path_local+"/Resultats_17PCIX.csv"))
Py4JJavaError Traceback (most recent call last)
<ipython-input-24-fed66bbb39c2> in <module>()
3 .option("header", "true")
4 .option("mode", "DROPMALFORMED")
----> 5 .load("file://"+csv_path_local+"/Resultats_17PCIX.csv"))
6
7 df_Csv.registerTempTable("df_Csv")
/usr/local/spark/python/pyspark/sql/readwriter.py in load(self, path, format, schema, **options)
164 self.options(**options)
165 if isinstance(path, basestring):
--> 166 return self._df(self._jreader.load(path))
167 elif path is not None:
168 if type(path) != list:
/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
/usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o382.load.
: scala.MatchError: 3.1.0 (of class java.lang.String)
at org.apache.spark.sql.hive.client.IsolatedClientLoader$.hiveVersion(IsolatedClientLoader.scala:89)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:300)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:287)
at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:66)
at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:65)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply$mcZ$sp(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:195)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:39)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog$lzycompute(HiveSessionStateBuilder.scala:54)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog(HiveSessionStateBuilder.scala:52)
at org.apache.spark.sql.hive.HiveSessionStateBuilder$$anon$1.<init>(HiveSessionStateBuilder.scala:69)
at org.apache.spark.sql.hive.HiveSessionStateBuilder.analyzer(HiveSessionStateBuilder.scala:69)
at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
at org.apache.spark.sql.internal.SessionState.analyzer$lzycompute(SessionState.scala:79)
at org.apache.spark.sql.internal.SessionState.analyzer(SessionState.scala:79)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
at org.apache.spark.sql.SparkSession.baseRelationToDataFrame(SparkSession.scala:432)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.createBaseDataset(CSVDataSource.scala:183)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.infer(CSVDataSource.scala:147)
at org.apache.spark.sql.execution.datasources.csv.CSVDataSource.inferSchema(CSVDataSource.scala:63)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:57)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:203)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:203)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:202)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:393)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:174)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
Я использую версию 2.3.2 spark с python 3.6, java 1.8 и hadoop 3.1.0