Created 01-11-2019 06:22 AM
Spark is getting data with a header showing col's A,C,D,B and the data under it. Next day we get the same data like this Col's B,D,A,C and then the next day we get data like col's A,C,B,D and so on randomly. Now we have to put this data in a hive table with col's as A,B,C,D. Can any one suggest me an idea how to write this script in spark?
Created 01-12-2019 02:40 AM
Read the CSV file with header as described here:
https://spark.apache.org/docs/2.1.0/api/python/pyspark.sql.html#pyspark.sql.DataFrameReader
Once you are able to read the csv file with header then use .select method and select the col's as
#pyspark:
df= spark.read.csv(<file>).option("header", "true") //read the csv with header df1=df.select("A","B","C","D") //select the columns in an order df1.write.mode("<overwrite/append>").saveAsTable("<db_name>.<tab_name>")
Created 01-12-2019 02:40 AM
Read the CSV file with header as described here:
https://spark.apache.org/docs/2.1.0/api/python/pyspark.sql.html#pyspark.sql.DataFrameReader
Once you are able to read the csv file with header then use .select method and select the col's as
#pyspark:
df= spark.read.csv(<file>).option("header", "true") //read the csv with header df1=df.select("A","B","C","D") //select the columns in an order df1.write.mode("<overwrite/append>").saveAsTable("<db_name>.<tab_name>")
Created 01-13-2019 10:18 PM
@Shu Thank you.