Semi-automatic Hive Metastore sync (#41) #63
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I tested it locally, but I'm not quite sure how to create a Hive database. |
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…ue-41 Semi-automatic Hive Metastore sync (#41)
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…definition (#63) This is a pretty huge refactor. Gone are `Projection` and `RichProjection`, and in its place we have a completely revamped and much simpler Dataset class. - The Dataset definition is now static. Columns cannot be added after the fact like before. - Unlike the complex Projection, which was based on a single Projection of a Dataset, and combined with input columns, a Dataset consists of data columns and partition columns, which are static and do not change - Computed column support has been removed - Column IDs are properly created on Dataset creation. They are used in place of names in the query API now, and in the C* chunks table. - When specifying the Dataset definition, you pass in "columnName:type" strings which are validated - It is now the responsibility of the input source / `IngestionStream` to map the input schema into partition and data columns matching the Dataset definition - `IngestRecord` now requires an `IngestRouting` which maps a flat column schema (like in CSV, Spark Rows, etc.) into an IngestRecord, figuring out the routing from input columns into partition/data columns. This is much much cleaner since the burden and complexity of input schema routing is removed from Dataset (formerly Projection) - version is removed from all APIs and Cassandra table schemas as well - The format of the ingestion source config and the dataset definition config have both changed - Remove ALL the unused imports!! This is now enforced by compiler. - SetupDataset now no longer takes a list of column names, due to simpler Dataset definition and IngestionStream responsibility to map incoming schema to Dataset dataColumns schema - As a result, no longer need to first get list of CSV file header column names, this can be done automatically :) - New cassandra schema; please drop old keyspaces - Kafka: RecordConverter API change
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This PR adds a feature to optionally automatically sync FiloDB datasets into a Hive Metastore database.
filodb.hive.database-nameconfig to specify the Hive metastore database to sync the FiloDB tables tofilodb.spark.syncToHive(sqlContext)This change should allow BI tools to be used with Spark Thrift Server via JDBC connection without the need to create temporary tables every time.