How to create hive table from Spark data frame, using its schema?

Question

I want to create a hive table using my Spark dataframe\'s schema. How can I do that?

For fixed columns, I can use:

val CreateTable_query = \"Create T         


        

Answer 1

Here is PySpark version to create Hive table from parquet file. You may have generated Parquet files using inferred schema and now want to push definition to Hive metastore. You can also push definition to the system like AWS Glue or AWS Athena and not just to Hive metastore. Here I am using spark.sql to push/create permanent table.

 # Location where my parquet files are present.
 df = spark.read.parquet("s3://my-location/data/")

    cols = df.dtypes
    buf = []
    buf.append('CREATE EXTERNAL TABLE test123 (')
    keyanddatatypes =  df.dtypes
    sizeof = len(df.dtypes)
    print ("size----------",sizeof)
    count=1;
    for eachvalue in keyanddatatypes:
        print count,sizeof,eachvalue
        if count == sizeof:
            total = str(eachvalue[0])+str(' ')+str(eachvalue[1])
        else:
            total = str(eachvalue[0]) + str(' ') + str(eachvalue[1]) + str(',')
        buf.append(total)
        count = count + 1

    buf.append(' )')
    buf.append(' STORED as parquet ')
    buf.append("LOCATION")
    buf.append("'")
    buf.append('s3://my-location/data/')
    buf.append("'")
    buf.append("'")
    ##partition by pt
    tabledef = ''.join(buf)

    print "---------print definition ---------"
    print tabledef
    ## create a table using spark.sql. Assuming you are using spark 2.1+
    spark.sql(tabledef);