Some of questions you have are related to which type of storage you are querying with Drill. If you are querying hive table, Drill uses Hive metastore API to get the metadata, and internally maintain a cache for speedup [1]. If you are querying parquet files through file system plugin, Drill has the concept of parquet metadata [2]. If you are querying other datasets, AFAIK, Drill does not maintain a metadata cache.
Drill's CTAS allows user to create partitioned data [3]. But you can also have your data created as partitioned table by other tools such as Hive, and Drill will recognize the hive partition from Hive metastore. Parquet files could be created by either Drill's CTAS, or other tools. I'm not clear what you mean in the fourth question, though. 1. https://drill.apache.org/docs/hive-metadata-caching/ 2. https://drill.apache.org/docs/optimizing-parquet-metadata-reading/ 3. https://drill.apache.org/docs/how-to-partition-data/ On Tue, Jul 25, 2017 at 12:54 AM, Divya Gehlot <[email protected]> wrote: > Hi, > As a naive user would like to know the benefitsof Apache Drill with tableau > ? > > As per my understanding we to visualize we need to push the data to tableau > for granular visualization . > > Would like to understand few features of Drill in terms of visualtion or > data retrieval : > 1, Metadata Caching > 2 .Partitioning > 3.Generation of Parquet File > 4.Custom column calculation. > > > Thanks, > Divya >
