In Hive-1.1.0, the supported compressions for ORC tables are NONE, ZLIB, SNAPPY and LZO. You may want to use Snappy or LZO compression on existing tables for different balance between compression ratio and decompression speed. Vertica does not support LZO compression for these formats. ORC tables are in zlib (Deflate in Impala) compression in default. When you have really huge volumes of data like data from IoT sensors for e.g., columnar formats like ORC and Parquet make a lot of sense since you need lower storage costs and fast retrieval. For files in Parquet format, Vertica supports some complex types.įiles compressed by Hive or Impala require Zlib (GZIP) or Snappy compression. Parquet and ORC also offer higher compression than Avro. CREATE TABLE newtable WITH ( format 'Parquet', writecompression 'SNAPPY' ) AS SELECT FROM oldtable The following example specifies that data in the table newtable be stored in ORC format using Snappy compression. Vertica supports all simple data types supported in Hive version 0.11 or later. If you export data from Vertica, consider exporting to one of these formats so that you can take advantage of their performance benefits when using external tables. If you have ORC or Parquet data, you can take advantage of optimizations including partition pruning and predicate pushdown. External tables with ORC or Parquet data therefore generally provide better performance then ones using delimited or other formats where the entire file must be scanned. If you want snappy, you can create the table in advance with property set to snappy compression and then take out -create-hcatalog-table More details are in this thread. The files contain metadata that allows Vertica to read only the portions that are needed for a query and to skip entire files. In this paper, we investigate on an execution time of query processing issues comparing two algorithm of ORC file: ZLIB and SNAPPY. This example uses default ORC compression. ORC and Parquet, like ROS in Vertica, are columnar formats. These formats are common among Hadoop users but are not restricted to Hadoop you can place Parquet files on S3, for example. It is my go-to compression algorithm for Apache file formats. Data in ORC files doesnt remain compressed after it is. The snappy compression type is supported by the AVRO, ORC and PARQUET file formats. Among them, Vertica is optimized for two columnar formats, ORC (Optimized Row Columnar) and Parquet. BigQuery supports the following compression codecs for ORC file contents: Zlib Snappy LZO LZ4. You can create external tables for data in any format that COPY supports.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |