I am trying to create dataframe with proper schema after fetching data from text file. in RDD, all data types are strings however one of the field data type is interger, which i want to ensure that created as integer. So i created Structtype and created dataframe. but it throws an error as below.
Error Message:
--------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) in () ----> 1 df.show()
/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in show(self, n, truncate, vertical) 376 """ 377 if isinstance(truncate, bool) and truncate: --> 378 print(self._jdf.showString(n, 20, vertical)) 379 else: 380 print(self._jdf.showString(n, int(truncate), vertical))
/Applications/anaconda2/lib/python2.7/site-packages/py4j/java_gateway.pyc in call(self, *args) 1284 answer = self.gateway_client.send_command(command) 1285 return_value = get_return_value( -> 1286 answer, self.gateway_client, self.target_id, self.name) 1287 1288 for temp_arg in temp_args:
/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/utils.pyc 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()
/Applications/anaconda2/lib/python2.7/site-packages/py4j/protocol.pyc 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 o64.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3.0 (TID 5, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main process() File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 393, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper return f(*args, **kwargs) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/session.py", line 730, in prepare verify_func(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1389, in verify verify_value(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1370, in verify_struct verifier(v) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1389, in verify verify_value(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1315, in verify_integer verify_acceptable_types(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1278, in verify_acceptable_types % (dataType, obj, type(obj)))) TypeError: field id: IntegerType can not accept object u'1' in type
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)
Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3383) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2544) at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2544) at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3364) at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3363) at org.apache.spark.sql.Dataset.head(Dataset.scala:2544) at org.apache.spark.sql.Dataset.take(Dataset.scala:2758) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254) at org.apache.spark.sql.Dataset.showString(Dataset.scala:291) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) 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(Thread.java:748) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main process() File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 393, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper return f(*args, **kwargs) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/session.py", line 730, in prepare verify_func(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1389, in verify verify_value(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1370, in verify_struct verifier(v) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1389, in verify verify_value(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1315, in verify_integer verify_acceptable_types(obj) File "/Users/nagaraju.n/spark-2.4.3-bin-hadoop2.7/python/pyspark/sql/types.py", line 1278, in verify_acceptable_types % (dataType, obj, type(obj)))) TypeError: field id: IntegerType can not accept object u'1' in type
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more
#!/usr/bin/env pythoncoding: utf-8
In[11]:
import os import sys from pyspark import SparkContext from pyspark.sql import SparkSession from pyspark.sql.types import * spark=SparkSession.builder.getOrCreate() sc = SparkContext.getOrCreate()
In[12]:
Reads data from file and creates rdd rdd=sc.textFile('/Users/nagaraju.n/Downloads/sample_data.txt')
In[13]:
type(rdd)
In[14]:
rdd_data=rdd.map(lambda p: p.split(","))
In[15]:
rdd_data.collect()
In[16]:
print(rdd_data)
In[17]:
orig_header=rdd_data.first()
In[18]:
type(orig_header)
In[19]:
rdd_withoutheader=rdd_data.filter(lambda p:p != orig_header)
In[20]:
rdd_withoutheader.collect()
In[21]:
Create Schema header = StructType([StructField("id", IntegerType(), True),StructField("first_name", StringType(),
True),StructField("last_name", StringType(), True),StructField("email", StringType(), True),StructField("phone", StringType(), True),StructField("city", StringType(), True),StructField("country", StringType(), True)])
In[22]:
header
In[23]:
df=spark.createDataFrame(rdd_withoutheader,header)
In[24]:
df.show()
