我正在使用pyspark对hive中的一个表进行文本分析。我使用以下代码

from pyspark.sql import SQLContext, Row, HiveContext
from pyspark.sql.functions import col, udf, StringType
from pyspark.sql.types import *
from pyspark import SparkContext
hc = HiveContext(sc)
df=hc.sql("select * from table1")
def cleaning_text(sentence):
   sentence=sentence.lower()
   sentence=re.sub('\'',' ',sentence)
   cleaned=' '.join([w for w in cleaned.split() if not len(w)<=2 ])
   return cleaned

org_val=udf(cleaning_text,StringType())
data=df.withColumn("cleaned",org_val(df.text))

data_1=data.select('uniqueid','cleaned','parsed')#2630789 #2022395
tokenizer = Tokenizer(inputCol="cleaned", outputCol="words")
wordsData = tokenizer.transform(data_1)

hc.sql("SET spark.sql.hive.convertMetastoreParquet=false")
hc.sql("create table table2 (uniqueid string, cleaned string, parsed string)")
wordsData.insertInto('table2')

我能做到

words_data.show(2)

然而，当我试图导出它时，它给了我这个错误

INFO FileOutputCommitter: FileOutputCommitter skip cleanup _temporary folders under output directory:false, ignore cleanup failures: false
Exception in thread "stdout writer for python" 17/02/02 15:18:44 ERROR Utils: Uncaught exception in thread stdout writer for python
java.lang.OutOfMemoryError: Java heap space

我不介意它是否也作为文本文件导出。