Spark dataframe save in single file on hdfs location [duplicate]

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It’s not possible using standard spark library, but you can use Hadoop API for managing filesystem – save output in temporary directory and then move file to the requested path. For example (in pyspark):

df.coalesce(1) \
    .write.format("com.databricks.spark.csv") \
    .option("header", "true") \
    .save("mydata.csv-temp")

from py4j.java_gateway import java_import
java_import(spark._jvm, 'org.apache.hadoop.fs.Path')

fs = spark._jvm.org.apache.hadoop.fs.FileSystem.get(spark._jsc.hadoopConfiguration())
file = fs.globStatus(sc._jvm.Path('mydata.csv-temp/part*'))[0].getPath().getName()
fs.rename(sc._jvm.Path('mydata.csv-temp/' + file), sc._jvm.Path('mydata.csv'))
fs.delete(sc._jvm.Path('mydata.csv-temp'), True)

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