在 PySpark 中使用 Flashtext 提取关键字

Question

我正在尝试从 PySpark 数据框中的一列菜单名称中提取关键字。

以下是关键字处理器的生成方式。 keywords 是关键字列表，例如 ['sandwiches', 'burgers', ...]。

from flashtext import KeywordProcessor

kp = KeywordProcessor()
for keyword in keywords:
    kp.add_keyword(keyword)

我定义了一个从菜单名称中提取关键字的函数。

def extractKeywords(menu_name, kp=kp):
    keywords = kp.extract_keywords(menu_name)
    return keywords

但是，当我尝试将此函数应用于我的 PySpark 数据帧时出现错误。

from pyspark.sql.functions import udf
from pyspark.sql.types import ArrayType, StringType

extractKeywords = udf(extractKeywords, ArrayType(StringType()))
df = df.withColumn("keywords_extracted", extractKeywords(df["menu_name"]))
df.show()

错误是这样的：

Py4JJavaError: An error occurred while calling o86.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0 (TID 87, localhost, executor driver): java.io.IOException: Cannot run program "
/Library/Frameworks/Python.framework/Versions/3.7/bin/python3.7
": error=2, No such file or directory
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
    at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:197)
    at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:122)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:95)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:109)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec.evaluate(BatchEvalPythonExec.scala:77)
    at org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute.apply(EvalPythonExec.scala:127)
    at org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute.apply(EvalPythonExec.scala:89)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$$anonfun$apply.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$$anonfun$apply.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun.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)
Caused by: java.io.IOException: error=2, No such file or directory
    at java.lang.UNIXProcess.forkAndExec(Native Method)
    at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
    at java.lang.ProcessImpl.start(ProcessImpl.java:134)
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
    ... 30 more

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.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$anon.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$$collectFromPlan(Dataset.scala:3389)
    at org.apache.spark.sql.Dataset$$anonfun$head.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun$head.apply(Dataset.scala:2550)
    at org.apache.spark.sql.Dataset$$anonfun.apply(Dataset.scala:3370)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId.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: java.io.IOException: Cannot run program "
/Library/Frameworks/Python.framework/Versions/3.7/bin/python3.7
": error=2, No such file or directory
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
    at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:197)
    at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:122)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:95)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:109)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec.evaluate(BatchEvalPythonExec.scala:77)
    at org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute.apply(EvalPythonExec.scala:127)
    at org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute.apply(EvalPythonExec.scala:89)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$$anonfun$apply.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$$anonfun$apply.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun.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
Caused by: java.io.IOException: error=2, No such file or directory
    at java.lang.UNIXProcess.forkAndExec(Native Method)
    at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
    at java.lang.ProcessImpl.start(ProcessImpl.java:134)
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
    ... 30 more

报错提示这可能是环境配置的问题。但是，PySpark 环境似乎还不错，因为我能够执行数据帧/Spark SQL 操作。谁能告诉我如何解决这个问题？谢谢！

Answer 1

我想通了：

kp = KeywordProcessor()
for keyword in keywords:
    kp.add_keyword(keyword)
df = df.withColumn(
    "extracted_keyword",
    udf(lambda x: kp.extract_keywords(x), ArrayType(StringType()))(orders.source_text_column)
)

在 PySpark 中使用 Flashtext 提取关键字

Keyword Extraction Using Flashtext in PySpark

pyspark-dataframes