What version of Spark you are using?
You can search "spark.sql.parquet.mergeSchema" on https://spark.apache.org/docs/latest/sql-programming-guide.html Starting from Spark 1.5, the default is already "false", which means Spark shouldn't scan all the parquet files to generate the schema. Yong Spark SQL and DataFrames - Spark 2.3.0 Documentation<https://spark.apache.org/docs/latest/sql-programming-guide.html> spark.apache.org Global Temporary View. Temporary views in Spark SQL are session-scoped and will disappear if the session that creates it terminates. If you want to have a temporary view that is shared among all sessions and keep alive until the Spark application terminates, you can create a global temporary view. ________________________________ From: Walid LEZZAR <walez...@gmail.com> Sent: Friday, April 27, 2018 7:42 AM To: spark users Subject: How to read the schema of a partitioned dataframe without listing all the partitions ? Hi, I have a parquet on S3 partitioned by day. I have 2 years of data (-> about 1000 partitions). With spark, when I just want to know the schema of this parquet without even asking for a single row of data, spark tries to list all the partitions and the nested partitions of the parquet. Which makes it very slow just to build the dataframe object on Zeppelin. Is there a way to avoid that ? Is there way to tell spark : "hey, just read a single partition and give me the schema of that partition and consider it as the schema of the whole dataframe" ? (I don't care about schema merge, it's off by the way) Thanks. Walid.
