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GH-38837: [Format] Add the specification to pass statistics through the Arrow C data interface #43553
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GH-38837: [Format] Add the specification to pass statistics through the Arrow C data interface #43553
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.. Licensed to the Apache Software Foundation (ASF) under one | ||
.. or more contributor license agreements. See the NOTICE file | ||
.. distributed with this work for additional information | ||
.. regarding copyright ownership. The ASF licenses this file | ||
.. to you under the Apache License, Version 2.0 (the | ||
.. "License"); you may not use this file except in compliance | ||
.. with the License. You may obtain a copy of the License at | ||
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.. http://www.apache.org/licenses/LICENSE-2.0 | ||
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.. Unless required by applicable law or agreed to in writing, | ||
.. software distributed under the License is distributed on an | ||
.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
.. KIND, either express or implied. See the License for the | ||
.. specific language governing permissions and limitations | ||
.. under the License. | ||
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.. _c-data-interface-statistics: | ||
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===================================================== | ||
Passing statistics through the Arrow C data interface | ||
===================================================== | ||
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Rationale | ||
========= | ||
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Statistics are useful for fast query processing. Many query engines | ||
use statistics to optimize their query plan. | ||
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Apache Arrow format doesn't have statistics but other formats that can | ||
be read as Apache Arrow data may have statistics. For example, the | ||
Apache Parquet C++ implementation can read an Apache Parquet file as | ||
Apache Arrow data and the Apache Parquet file may have statistics. | ||
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One of :ref:`c-data-interface` use cases is the following: | ||
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1. Module A reads Apache Parquet file as Apache Arrow data. | ||
2. Module A passes the read Apache Arrow data to module B through the | ||
Arrow C data interface. | ||
3. Module B processes the passed Apache Arrow data. | ||
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If module A can pass the statistics associated with the Apache Parquet | ||
file to module B through the Arrow C data interface, module B can use | ||
the statistics to optimize its query plan. | ||
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Goals | ||
----- | ||
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* Establish a standard way to pass statistics through the Arrow C data | ||
interface. | ||
* Provide this in a manner that enables compatibility and ease of | ||
implementation for existing users of the Arrow C data interface. | ||
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Non-goals | ||
--------- | ||
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* Provide a common way to pass statistics that can be used for | ||
other interfaces such Arrow Flight too. | ||
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For example, ADBC has `the statistics related APIs | ||
<https://arrow.apache.org/adbc/current/format/specification.html#statistics>`__. | ||
This specification doesn't replace them. | ||
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This specification may fit some use cases of :ref:`format-ipc` not the | ||
Arrow data interface. But we don't recommend this specification for | ||
the Arrow IPC format for now. Because we may be able to define better | ||
specification for the Arrow IPC format. The Arrow IPC format has some | ||
different features compared with the Arrow C data interface. For | ||
example, the Arrow IPC format can have :ref:`ipc-message-format | ||
metadata for each message`. If you're interested in the specification | ||
for passing statistics through the Arrow IPC format, please start a | ||
discussion on the `Arrow development mailing-list | ||
<https://arrow.apache.org/community/>`__. | ||
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.. _c-data-interface-statistics-schema: | ||
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Schema | ||
====== | ||
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This specification provides only the schema for statistics. The | ||
producer passes statistics through the Arrow C data interface as an | ||
Arrow map array that uses this schema. | ||
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Here is the outline of the schema for statistics:: | ||
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struct< | ||
column: int32, | ||
statistics: map< | ||
key: dictionary< | ||
indices: int32, | ||
dictionary: utf8 | ||
>, | ||
items: dense_union<...all needed types...>, | ||
> | ||
> | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Does this mean we get an array of maps or a single map? Because we really only need a single map. Any consumer of these statistics will loop through the values and gather only the statistic values that it cares about by skipping the keys that it doesn't understand. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. An (one element) array of maps. But we can simplify this. I didn't notice it. Thanks. How about the following? It removes the outer
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. That looks reasonable to me! There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I've updated this part! |
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Here is the details of top-level ``struct``: | ||
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.. list-table:: | ||
:header-rows: 1 | ||
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* - Name | ||
- Data type | ||
- Nullable | ||
- Notes | ||
* - ``column`` | ||
- ``int32`` | ||
- ``true`` | ||
- The zero-based column index, or null if the statistics | ||
describe the whole table or record batch. | ||
* - ``statistics`` | ||
- ``map`` | ||
- ``false`` | ||
- Statistics for the target column, table or record batch. See | ||
the separate table below for details. | ||
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Here is the details of the ``map`` of the ``statistics``: | ||
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.. list-table:: | ||
:header-rows: 1 | ||
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* - Key or items | ||
- Data type | ||
- Nullable | ||
- Notes | ||
* - key | ||
- ``dictionary<indices: int32, dictionary: utf8>`` | ||
- ``false`` | ||
- Statistics key is string. Dictionary is used for | ||
efficiency. Different keys are assigned for exact value and | ||
approximate value. Also see the separate description below for | ||
statistics key. | ||
* - items | ||
- ``dense_union`` | ||
- ``false`` | ||
- Statistics value is dense union. It has at least all needed | ||
types based on statistics kinds in the keys. For example, you | ||
need at least ``int64`` and ``float64`` types when you have a | ||
``int64`` distinct count statistic and a ``float64`` average | ||
byte width statistic. Also see the separate description below | ||
for statistics key. | ||
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We don't standardize field names for the dense union because | ||
consumers can access to proper field by index not name. So | ||
producers can use any valid name for fields. | ||
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.. _c-data-interface-statistics-key: | ||
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Statistics key | ||
-------------- | ||
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Statistics key is string. ``dictionary<int32, utf8>`` is used for | ||
efficiency. | ||
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We assign different statistics keys for variants instead of using | ||
flags. For example, we assign different statistics keys for exact | ||
value and approximate value. | ||
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The colon symbol ``:`` is to be used as a namespace separator like | ||
:ref:`format_metadata`. It can be used multiple times in a key. | ||
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The ``ARROW`` pattern is a reserved namespace for pre-defined | ||
statistics keys. User-defined statistics must not use it. | ||
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Here are pre-defined statistics keys: | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. They are the same as ADBC's one: https://github.com/apache/arrow-adbc/blob/05fa60d643c66b572d426ab28aa78fc52e9520e8/c/include/arrow-adbc/adbc.h#L524-L570 |
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.. list-table:: | ||
:header-rows: 1 | ||
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* - Key | ||
- Data type | ||
- Notes | ||
* - ``ARROW:average_byte_width:exact`` | ||
- ``float`` | ||
- The average size in bytes of a row in the target. (exact) | ||
* - ``ARROW:average_byte_width:approximate`` | ||
- ``float64`` | ||
- The average size in bytes of a row in the target. (approximate) | ||
* - ``ARROW:distinct_count:exact`` | ||
- ``int64`` | ||
- The number of distinct values in the target. (exact) | ||
* - ``ARROW:distinct_count:approximate`` | ||
- ``float64`` | ||
- The number of distinct values in the target. (approximate) | ||
* - ``ARROW:max_byte_width:exact`` | ||
- ``int64`` | ||
- The maximum size in bytes of a row in the target. (exact) | ||
* - ``ARROW:max_byte_width:approximate`` | ||
- ``float64`` | ||
- The maximum size in bytes of a row in the target. (approximate) | ||
* - ``ARROW:max_value:exact`` | ||
- Target dependent | ||
- The maximum value in the target. (exact) | ||
* - ``ARROW:max_value:approximate`` | ||
- Target dependent | ||
- The maximum value in the target. (approximate) | ||
* - ``ARROW:min_value:exact`` | ||
- Target dependent | ||
- The minimum value in the target. (exact) | ||
* - ``ARROW:min_value:approximate`` | ||
- Target dependent | ||
- The minimum value in the target. (approximate) | ||
* - ``ARROW:null_count:exact`` | ||
- ``int64`` | ||
- The number of nulls in the target. (exact) | ||
* - ``ARROW:null_count:approximate`` | ||
- ``float64`` | ||
- The number of nulls in the target. (approximate) | ||
* - ``ARROW:row_count:exact`` | ||
- ``int64`` | ||
- The number of rows in the target table or record batch. (exact) | ||
* - ``ARROW:row_count:approximate`` | ||
- ``float64`` | ||
- The number of rows in the target table or record | ||
batch. (approximate) | ||
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If you find a missing statistics key that is usable for multiple | ||
systems, please propose it on the `Arrow development mailing-list | ||
<https://arrow.apache.org/community/>`__. | ||
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Examples | ||
-------- | ||
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TODO: Add at least C++ example. |
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What about the Arrow IPC format? Can you add a sentence here that explains why we do not recommend using this to pass statistics over Arrow IPC?
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Good point. This may fit the Arrow IPC format. (A producer sends data and statistics as 2 separated the Arrow IPC format data.)
But the Arrow IPC format can use more approaches. For example, the Arrow IPC format can have metadata for each record batch data: https://arrow.apache.org/docs/format/Columnar.html#encapsulated-message-format (The Arrow C data can't have metadata for
ArrowArray
.)The Arrow IPC format can be used with other mechanisms such as Arrow Flight and ADBC.
So this may not be the best approach for the Arrow IPC format. We should discuss this use case with the Arrow IPC format separately.
I'll add something to here.