Hi Chetan,
You can use
spark-submit showDF.py | hadoop fs -put - showDF.txt
showDF.py:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("Write stdout").getOrCreate()
spark.sparkContext.setLogLevel("OFF")
spark.table("").show(100,truncate=false)
But is there any
Are you sure you only need 10 partitions? Do you get the same performance
writing to HDFS with 10 partitions?
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Writing to CSV is very slow.
>From what I've seen this is the preferred way to write to hive ;
myDf.createOrReplaceTempView("mytempTable")
sqlContext.sql("create table mytable as select * from mytempTable");
Source :
Before we can confirm that the issue is skewed data, let’s confirm it :
import org.apache.spark.sql.functions.spark_partition_id
df.groupBy(spark_partition_id).count
This should give the number of records you have in each partition.
From: Sagar Grover
Sent: Thursday, April
Hi,
Please can you let me know which of the following options
would be a best practice for writing data into a Hive table :
Option 1:
outputDataFrame.write
.mode(SaveMode.Overwrite)
.format("csv")
.save("hdfs_path")
Option 2: Get the data from a dataframe and
Hi Spark community!
As you know ApacheCon NA 2019 is coming this Sept and it’s CFP is now open!
This is an important milestone as we celebrate 20 years of ASF. We have tracks
like Big Data and Machine Learning among many others. Please submit your
talks/thoughts/challenges/learnings here:
Hi Spark users, especially Structured Streaming users who are dealing with
stateful queries,
I'm pleased to introduce Spark State Tools, which enables offline state
manipulations for structured streaming query.
Basically the tool provides state as batch source and output so that you
can read
Hello Users,
In spark when I have a DataFrame and do .show(100) the output which gets
printed, I wants to save as it is content to txt file in HDFS.
How can I do this?
Thanks
