Spark的快速数字哈希函数（PySpark）

我试图将哈希函数应用于PySpark数据帧（在EMR集群上运行）列中的短字符串，并获取一个数值作为新列。例如，CRC3将完成这项工作。我知道，但它在Scala中，我需要一个python版本

（顺便说一句，我知道pyspark.sql.functions中的sha1和sha2，但我需要一个更快的哈希函数，它只返回一个数字，比如校验和（但冲突越小越好）。）

我已经做了以下工作：

import zlib
crc32 = udf(zlib.crc32)
df2= df.withColumn("crc32", crc32(col("Col1")))
df2.show()

我得到了一个错误：

    Py4JJavaError: An error occurred while calling o873.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 37.0 failed 4 times, most recent failure: Lost task 0.3 in stage 37.0 (TID 45019, ip-172-31-58-134.ec2.internal, executor 181): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 345, in dump_stream
    self.serializer.dump_stream(self._batched(iterator), stream)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 334, in _batched
    for item in iterator:
  File "<string>", line 1, in <lambda>
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
    return lambda *a: f(*a)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/util.py", line 113, in wrapper
    return f(*args, **kwargs)
TypeError: a bytes-like object is required, not 'str'

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
    at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    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$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:291)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:283)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$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$$failJobAndIndependentStages(DAGScheduler.scala:2041)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2029)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2028)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2028)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:966)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:966)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2262)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2211)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2200)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:777)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:401)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
    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:3369)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2764)
    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 "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 345, in dump_stream
    self.serializer.dump_stream(self._batched(iterator), stream)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py", line 334, in _batched
    for item in iterator:
  File "<string>", line 1, in <lambda>
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
    return lambda *a: f(*a)
  File "/mnt1/yarn/usercache/zeppelin/appcache/application_1571175019959_0009/container_1571175019959_0009_01_000182/pyspark.zip/pyspark/util.py", line 113, in wrapper
    return f(*args, **kwargs)
TypeError: a bytes-like object is required, not 'str'

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
    at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    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$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:291)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:283)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$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

(<class 'py4j.protocol.Py4JJavaError'>, Py4JJavaError('An error occurred while calling o873.showString.\n', JavaObject id=o874), <traceback object at 0x7f69d17ff508>)
 SPARK JOB ERROR   

Py4JJavaError:调用o873.showString时出错。
：org.apache.spark.sparkeexception:作业因阶段失败而中止：阶段37.0中的任务0失败4次，最近的失败：阶段37.0中的任务0.3丢失（TID 45019，ip-172-31-58-134.ec2.internal，executor 181）：org.apache.spark.api.python异常：回溯（最近一次调用）：
文件“/mnt1/thread/usercache/zeppelin/appcache/application_1571755019959_0009/container_1571755019959_0009_01_000182/pyspark.zip/pyspark/worker.py”，主行377
过程（）
文件“/mnt1/thread/usercache/zeppelin/appcache/application_157175019959_0009/container_157175019959_0009_01_000182/pyspark.zip/pyspark/worker.py”，第372行，正在处理中
serializer.dump_流（func（拆分索引，迭代器），outfile）
文件“/mnt1/thread/usercache/zeppelin/appcache/application_157175019959_0009/container_157175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py”，第345行，转储流中
self.serializer.dump_流（self._批处理（迭代器），流）
文件“/mnt1/thread/usercache/zeppelin/appcache/application_1571755019959_0009/container_1571755019959_0009_01_000182/pyspark.zip/pyspark/serializers.py”，第141行，转储流中
对于迭代器中的obj：
文件“/mnt1/thread/usercache/zeppelin/appcache/application_157175019959_0009/container_157175019959_0009_01_000182/pyspark.zip/pyspark/serializers.py”，第334行，分批
对于迭代器中的项：
文件“”，第1行，在
文件“/mnt1/thread/usercache/zeppelin/appcache/application_157175019959_0009/container_157175019959_0009_01_000182/pyspark.zip/pyspark/worker.py”，第85行，in
返回λ*a:f（*a）
文件“/mnt1/thread/usercache/zeppelin/appcache/application_157175019959_0009/container_157175019959_0009_01_000182/pyspark.zip/pyspark/util.py”，第113行，在包装器中
返回f（*args，**kwargs）
TypeError:需要类似字节的对象，而不是“str”
位于org.apache.spark.api.python.BasePythonRunner$readeriator.handlePythonException（PythonRunner.scala:456）
位于org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read（PythonUDFRunner.scala:81）
位于org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read（PythonUDFRunner.scala:64）
位于org.apache.spark.api.python.BasePythonRunner$readerierator.hasNext（PythonRunner.scala:410）
在org.apache.spark.interruptblediator.hasNext（interruptblediator.scala:37）
位于scala.collection.Iterator$$anon$12.hasNext（Iterator.scala:440）
位于scala.collection.Iterator$$anon$11.hasNext（Iterator.scala:409）
位于scala.collection.Iterator$$anon$11.hasNext（Iterator.scala:409）
位于org.apache.spark.sql.catalyst.expressions.GeneratedClass$GenerateEditorForCodeGenStage1.processNext（未知源）
位于org.apache.spark.sql.execution.BufferedRowIterator.hasNext（BufferedRowIterator.java:43）
位于org.apache.spark.sql.execution.whisttagecodegenexec$$anonfun$13$$anon$1.hasNext（whisttagecodegenexec.scala:636）
位于org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply（SparkPlan.scala:291）
位于org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply（SparkPlan.scala:283）
位于org.apache.spark.rdd.rdd$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply（rdd.scala:836）
位于org.apache.spark.rdd.rdd$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply（rdd.scala:836）
位于org.apache.spark.rdd.MapPartitionsRDD.compute（MapPartitionsRDD.scala:52）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:324）
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:288）
位于org.apache.spark.rdd.MapPartitionsRDD.compute（MapPartitionsRDD.scala:52）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:324）
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:288）
位于org.apache.spark.scheduler.ResultTask.runTask（ResultTask.scala:90）
位于org.apache.spark.scheduler.Task.run（Task.scala:123）
位于org.apache.spark.executor.executor$TaskRunner$$anonfun$10.apply（executor.scala:408）
位于org.apache.spark.util.Utils$.tryWithSafeFinally（Utils.scala:1360）
位于org.apache.spark.executor.executor$TaskRunner.run（executor.scala:414）
位于java.util.concurrent.ThreadPoolExecutor.runWorker（ThreadPoolExecutor.java:1149）
位于java.util.concurrent.ThreadPoolExecutor$Worker.run（ThreadPoolExecutor.java:624）
运行（Thread.java:748）
驱动程序堆栈跟踪：
位于org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages（DAGScheduler.scala:2041）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply（DAGScheduler.scala:2029）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply（DAGScheduler.scala:2028）
位于scala.collection.mutable.resizeblearray$class.foreach（resizeblearray.scala:59）
位于scala.collection.mutable.ArrayBuffer.foreach（ArrayBuffer.scala:48）
位于org.apache.spark.scheduler.DAGScheduler.abortStage（DAGScheduler.scala:2028）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply（DAGScheduler.scala:966）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply（DAGScheduler.scala:966）
位于scala.Option.foreach（Option.scala:257）
位于org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed（DAGScheduler.scala:966）
位于org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive（DAGScheduler.scala:2262）
在org.apache.spark.scheduler上
import pyspark.sql.functions as F

df2= df.withColumn("hash", F.hash(col("Col1")))
df2.show()