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When Hive (and probably other engines as well) converts a legacy Hive table to Iceberg it doesn't rewrite the data files. It means that the data files don't have write ids neither partition column data. Currently Impala expects the partition columns to be present in the data files, so it is not able to read converted partitioned tables. With this patch Impala loads partition values from the Iceberg metadata. The extra metadata information is attached to the file descriptor objects and propageted to the scanners. This metadata contains the Iceberg data file format (later it could be used to handle mixed-format tables), and partition data. We use the partition data in the HdfsScanner to create the template tuple that contains the partition values of identity-partitioned columns. This is not only true to migrated tables, but all Iceberg tables with identity partitions, which means we also save some IO and CPU time for such columns. The partition information could also be used for Dynamic Partition Pruning later. We use the (human-readable) string representation of the partition data when storing them in the flat buffers. This helps debugging, also it provides the needed flexibility when the partition columns evolve (e.g. INT -> BIGINT, DECIMAL(4,2) -> DECIMAL(6,2)). Testing * e2e test for all data types that can be used to partition a table * e2e test for migrated partitioned table + schema evolution (without renaming columns) * e2e for table where all columns are used as identity-partitions Change-Id: Iac11a02de709d43532056f71359c49d20c1be2b8 Reviewed-on: http://gerrit.cloudera.org:8080/18240 Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com> Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
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
DEPENDENT_LOAD_ACID
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.