Thanks Cheng, that makes sense. So for new dataframe creation (not conversion from Avro but from JSON or CSV inputs) in Spark we shouldn't worry about using Avro at all, just use the Spark SQL StructType when building new Dataframes? If so, that will be a lot simpler!
Thanks, Ewan From: Cheng Lian [mailto:lian.cs....@gmail.com] Sent: 19 May 2015 11:01 To: Ewan Leith; user@spark.apache.org Subject: Re: AvroParquetWriter equivalent in Spark 1.3 sqlContext Save or createDataFrame Interfaces? Hi Ewan, Different from AvroParquetWriter, in Spark SQL we uses StructType as the intermediate schema format. So when converting Avro files to Parquet files, we internally converts Avro schema to Spark SQL StructType first, and then convert StructType to Parquet schema. Cheng On 5/19/15 4:42 PM, Ewan Leith wrote: Hi all, I might be missing something, but does the new Spark 1.3 sqlContext save interface support using Avro as the schema structure when writing Parquet files, in a similar way to AvroParquetWriter (which I've got working)? I've seen how you can load an avro file and save it as parquet from https://databricks.com/blog/2015/03/24/spark-sql-graduates-from-alpha-in-spark-1-3.html, but not using the 2 together. Thanks, and apologies if I've missed something obvious! Ewan
