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impala/testdata/datasets
Attila Jeges 27fa27e808 IMPALA-8198: DATE: Read from avro.
This change is a follow-up to IMPALA-7368 and adds support for DATE
type to the avro scanner.

Similarly to parquet, avro uses DATE logical type for dates. DATE
logical type annotates an INT32 that stores the number of days since
the unix epoch, 1 January 1970.

This representation introduces an avro interoperability issue between
Impala and older versions of Hive:
- Before version 3.1, Hive used Julian calendar to represent dates
  up to 1582-10-05 and Gregorian calendar for dates starting with
  1582-10-15. Dates between 1582-10-05 and 1582-10-15 were lost.
- Impala uses proleptic Gregorian calendar, extending the Gregorian
  calendar backward to dates preceding its official introduction in
  1582-10-15.
This means that pre-1582-10-15 dates written to an avro table by Hive
will be read back incorrectly by Impala.

Note that Hive 3.1 switched to proleptic Gregorian calendar too, so
for Hive 3.1+ this is no longer an issue.

Dependency changes:
- BE uses avro 1.7.4-p5 from native-toolchain.

Change-Id: I7a9d5b93a22cf3a00244037e187f8c145cacc959
Reviewed-on: http://gerrit.cloudera.org:8080/13944
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
2019-09-27 17:18:35 +00:00
..
2019-04-25 23:39:53 +00:00
2019-04-25 23:39:53 +00:00

This directory contains Impala test data sets. The directory layout is structured as follows:

datasets/
   <data set>/<data set>_schema_template.sql
   <data set>/<data files SF1>/data files
   <data set>/<data files SF2>/data files

Where SF is the scale factor controlling data size. This allows for scaling the same schema to
different sizes based on the target test environment.

The schema template SQL files have the following format:

  The goal is to provide a single place to define a table + data files
  and have the schema and data load statements generated for each combination of file
  format, compression, etc. The way this works is by specifying how to create a
  'base table'. The base table can be used to generate tables in other file formats
  by performing the defined INSERT / SELECT INTO statement. Each new table using the
  file format/compression combination needs to have a unique name, so all the
  statements are pameterized on table name.
  The template file is read in by the 'generate_schema_statements.py' script to
  to generate all the schema for the Imapla benchmark tests.

  Each table is defined as a new section in the file with the following format:

  ====
  ---- SECTION NAME
  section contents
  ...
  ---- ANOTHER SECTION
  ... section contents
  ---- ... more sections...

  Note that tables are delimited by '====' and that even the first table in the
  file must include this header line.

  The supported section names are:

  DATASET
      Data set name - Used to group sets of tables together
  BASE_TABLE_NAME
      The name of the table within the database
  CREATE
      Explicit CREATE statement used to create the table (executed by Impala)
  CREATE_HIVE
      Same as the above, but will be executed by Hive instead. If specified,
      'CREATE' must not be specified.
  CREATE_KUDU
      Customized CREATE TABLE statement used to create the table for Kudu-specific
      syntax.

  COLUMNS
  PARTITION_COLUMNS
  ROW_FORMAT
  HBASE_COLUMN_FAMILIES
  TABLE_PROPERTIES
  HBASE_REGION_SPLITS
      If no explicit CREATE statement is provided, a CREATE statement is generated
      from these sections (see 'build_table_template' function in
      'generate-schema-statements.py' for details)

  ALTER
      A set of ALTER statements to be executed after the table is created
      (typically to add partitions, but may also be used for other settings that
      cannot be specified directly in the CREATE TABLE statement).

      These statements are ignored for HBase and Kudu tables.

  LOAD
      The statement used to load the base (text) form of the table. This is
      typically a LOAD DATA statement.

  DEPENDENT_LOAD
  DEPENDENT_LOAD_KUDU
  DEPENDENT_LOAD_HIVE
      Statements to be executed during the "dependent load" phase. These statements
      are run after the initial (base table) load is complete.

  HIVE_MAJOR_VERSION
       The required major version of Hive for this table. If the major version
       of Hive at runtime does not exactly match the version specified in this section,
       the table will be skipped.

       NOTE: this is not a _minimum_ version -- if HIVE_MAJOR_VERSION specifies '2',
                   the table will _not_ be loaded/created on Hive 3.