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This patch adds support to INSERT INTO identity-partitioned Iceberg tables. Identity-partitioned Iceberg tables are similar to regular partitioned tables, they are even stored in the same directory structure. The difference is that the data files still store the partitioning columns. The INSERT INTO syntax is similar to the syntax for non-partitioned tables, i.e.: INSERT INTO <iceberg_tbl> VALUES (<val1>, <val2>, <val3>, ...); Or, INSERT INTO <iceberg_tbl> SELECT <val1>, <val2>, ... FROM <source_tbl> (please note that we don't use the PARTITION keyword) The values must be in column order corresponding to the table schema. Impala will automatically create/find the partitions based on the Iceberg partition spec. Partitioned Iceberg tables are stored as non-partitioned tables in the Hive Metastore (similarly to partitioned Kudu tables). However, the InsertStmt still generates the partition expressions for them. These partition expressions are used to shuffle and sort the input data so we don't end up writing too many files. The HdfsTableSink also uses the partition expressions to write the data files with the proper partition paths. Iceberg is able to parse the partition paths to generate the corresponding metadata for the partitions. This happens at the end in IcebergCatalogOpExecutor. Testing: * added planner test to verify shuffling and sorting * added negative tests for unsupported features like PARTITION clause and non-identity partition transforms * e2e tests with partitioned inserts Change-Id: If98797a2bfdc038d0467c8f83aadf1a12e1d69d4 Reviewed-on: http://gerrit.cloudera.org:8080/16825 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.