[
https://issues.apache.org/jira/browse/ARROW-3564?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hatem Helal updated ARROW-3564:
-------------------------------
Description:
Using pyarrow v0.11.0, the following script writes a simple table (lifted from
the [pyarrow doc|https://arrow.apache.org/docs/python/parquet.html]) to both
parquet format versions 1.0 and 2.0, with and without dictionary encoding
enabled.
{{import}}{{ }}{{pyarrow.parquet as pq}}
{{import}}{{ }}{{numpy as np}}
{{import}}{{ }}{{pandas as pd}}
{{import}}{{ }}{{pyarrow as pa}}
{{import}}{{ }}{{itertools}}{{}}
{{df }}{{=}} {{pd.DataFrame({}}{{'one'}}{{: [}}\{{-}}\{{1}}\{{, np.nan,
}}\{{2.5}}{{],}}
{{ }}{{'two'}}{{: [}}\{{'foo'}}\{{, }}\{{'bar'}}\{{, }}\{{'baz'}}{{],}}
{{ }}{{'three'}}{{: [}}\{{True}}\{{, }}\{{False}}\{{, }}\{{True}}{{]},}}
{{ }}{{index}}{{=}}{{list}}{{(}}{{'abc'}}{{))}}
{{table }}{{=}} {{pa.Table.from_pandas(df)}}
{{use_dict }}{{=}} {{[}}\\{{True}}\\{{, }}\\{{False}}{{]}}
{{version }}{{=}} {{[}}\\{{'1.0'}}\\{{, }}\\{{'2.0'}}{{]}}
{{for}} {{tf, v }}{{in}} {{itertools.product(use_dict, version):}}
{{ }}{{filename }}{{=}} {{'example_v'}} +{{v}}+ {{'_dict_'}}
+{{str}}{{(tf)}}+ {{'.parquet'}}
{{ }}{{pq.write_table(table, filename, use_dictionary}}{{=}}{{tf,
version}}{{=}}{{v)}}|
Inspecting the written files using
[parquet-tools|https://github.com/apache/parquet-mr/tree/master/parquet-tools]
appears to show that dictionary encoding is not used in either of the version
2.0 files. Both files report that the columns are encoded using {{PLAIN,RLE}}
and that the dictionary page offset is zero. I was expecting that the column
encoding would include {{RLE_DICTIONARY}}. Attached are the script with repro
steps and the files that were generated by it.
Below is the output of using {{parquet-tools meta}} on the version 2.0 files
{panel:title=version='2.0', use_dictionary = True}
{panel}
|{{% parquet-tools meta example_v2.0_dict_True.parquet}}
{{file:
[file:.../example_v2.0_dict_True.parquet|file:///.../example_v2.0_dict_True.parquet]}}
{{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
\{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
"name": "one", "numpy_type": "float64", "pandas_type": "float64"}
, {"metadata": null, "field_name": "three", "name": "three", "numpy_type":
"bool", "pandas_type": "bool"}
, {"metadata": null, "field_name": "two", "name": "two", "numpy_type":
"object", "pandas_type": "bytes"}
, {"metadata": null, "field_name": "__index_level_0__", "name": null,
"numpy_type": "object", "pandas_type": "bytes"}
], "column_indexes": [\\\{"metadata": null, "field_name": null, "name": null,
"numpy_type": "object", "pandas_type": "bytes"}|file://%7B/]}}}
{{file schema: schema}}
{{--------------------------------------------------------------------------------}}
{{one: OPTIONAL DOUBLE R:0 D:1}}
{{three: OPTIONAL BOOLEAN R:0 D:1}}
{{two: OPTIONAL BINARY R:0 D:1}}
{{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
{{row group 1: RC:3 TS:211 OFFSET:4}}
{{--------------------------------------------------------------------------------}}
{{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
{{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
{{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
{{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
{panel:title=version='2.0', use_dictionary = False}
{panel}
|{{% parquet-tools meta example_v2.0_dict_False.parquet}}
{{file:
[file:.../example_v2.0_dict_False.parquet|file:///.../example_v2.0_dict_False.parquet]}}
{{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
\{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
"name": "one", "numpy_type": "float64", "pandas_type": "float64"}
, {"metadata": null, "field_name": "three", "name": "three", "numpy_type":
"bool", "pandas_type": "bool"}
, {"metadata": null, "field_name": "two", "name": "two", "numpy_type":
"object", "pandas_type": "bytes"}
, {"metadata": null, "field_name": "__index_level_0__", "name": null,
"numpy_type": "object", "pandas_type": "bytes"}
], "column_indexes": [\\\{"metadata": null, "field_name": null, "name": null,
"numpy_type": "object", "pandas_type": "bytes"}|file://%7B/]}}}
{{file schema: schema}}
{{--------------------------------------------------------------------------------}}
{{one: OPTIONAL DOUBLE R:0 D:1}}
{{three: OPTIONAL BOOLEAN R:0 D:1}}
{{two: OPTIONAL BINARY R:0 D:1}}
{{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
{{row group 1: RC:3 TS:211 OFFSET:4}}
{{--------------------------------------------------------------------------------}}
{{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
{{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
{{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
{{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
was:
Using pyarrow v0.11.0, the following script writes a simple table (lifted from
the [pyarrow doc|https://arrow.apache.org/docs/python/parquet.html]) to both
parquet format versions 1.0 and 2.0, with and without dictionary encoding
enabled.
|{{import}} {{pyarrow.parquet as pq}}
{{import}} {{numpy as np}}
{{import}} {{pandas as pd}}
{{import}} {{pyarrow as pa}}
{{import}} {{itertools}}
{{df }}{{=}} {{pd.DataFrame({}}{{'one'}}{{: [}}{{-}}{{1}}{{, np.nan,
}}{{2.5}}{{],}}
{{ }}{{'two'}}{{: [}}{{'foo'}}{{, }}{{'bar'}}{{, }}{{'baz'}}{{],}}
{{ }}{{'three'}}{{: [}}{{True}}{{, }}{{False}}{{, }}{{True}}{{]},}}
{{ }}{{index}}{{=}}{{list}}{{(}}{{'abc'}}{{))}}
{{table }}{{=}} {{pa.Table.from_pandas(df)}}
{{use_dict }}{{=}} {{[}}\{{True}}\{{, }}\{{False}}{{]}}
{{version }}{{=}} {{[}}\{{'1.0'}}\{{, }}\{{'2.0'}}{{]}}
{{for}} {{tf, v }}{{in}} {{itertools.product(use_dict, version):}}
{{ }}{{filename }}{{=}} {{'example_v'}} {+} {{v }}{+} {{'_dict_'}} {+}
{{str}}{{(tf) }}{+} {{'.parquet'}}
{{ }}{{pq.write_table(table, filename, use_dictionary}}{{=}}{{tf,
version}}{{=}}{{v)}}|
Inspecting the written files using
[parquet-tools|https://github.com/apache/parquet-mr/tree/master/parquet-tools]
appears to show that dictionary encoding is not used in either of the version
2.0 files. Both files report that the columns are encoded using {{PLAIN,RLE}}
and that the dictionary page offset is zero. I was expecting that the column
encoding would include {{RLE_DICTIONARY}}. Attached are the script with repro
steps and the files that were generated by it.
Below is the output of using {{parquet-tools meta}} on the version 2.0 files
{panel:title=version='2.0', use_dictionary = True}
{panel}
|{{% parquet-tools meta example_v2.0_dict_True.parquet}}
{{file:
[file:.../example_v2.0_dict_True.parquet|file:///.../example_v2.0_dict_True.parquet]}}
{{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
"name": "one", "numpy_type": "float64", "pandas_type": "float64"},
\\{"metadata": null, "field_name": "three", "name": "three", "numpy_type":
"bool", "pandas_type": "bool"}, \\{"metadata": null, "field_name": "two",
"name": "two", "numpy_type": "object", "pandas_type": "bytes"}, \\{"metadata":
null, "field_name": "__index_level_0__", "name": null, "numpy_type": "object",
"pandas_type": "bytes"}], "column_indexes": [\\{"metadata": null, "field_name":
null, "name": null, "numpy_type": "object", "pandas_type": "bytes"}]}}}
{{file schema: schema}}
{{--------------------------------------------------------------------------------}}
{{one: OPTIONAL DOUBLE R:0 D:1}}
{{three: OPTIONAL BOOLEAN R:0 D:1}}
{{two: OPTIONAL BINARY R:0 D:1}}
{{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
{{row group 1: RC:3 TS:211 OFFSET:4}}
{{--------------------------------------------------------------------------------}}
{{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
{{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
{{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
{{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
{panel:title=version='2.0', use_dictionary = False}
{panel}
|{{% parquet-tools meta example_v2.0_dict_False.parquet}}
{{file:
[file:.../example_v2.0_dict_False.parquet|file:///.../example_v2.0_dict_False.parquet]}}
{{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
"name": "one", "numpy_type": "float64", "pandas_type": "float64"},
\\{"metadata": null, "field_name": "three", "name": "three", "numpy_type":
"bool", "pandas_type": "bool"}, \\{"metadata": null, "field_name": "two",
"name": "two", "numpy_type": "object", "pandas_type": "bytes"}, \\{"metadata":
null, "field_name": "__index_level_0__", "name": null, "numpy_type": "object",
"pandas_type": "bytes"}], "column_indexes": [\\{"metadata": null, "field_name":
null, "name": null, "numpy_type": "object", "pandas_type": "bytes"}]}}}
{{file schema: schema}}
{{--------------------------------------------------------------------------------}}
{{one: OPTIONAL DOUBLE R:0 D:1}}
{{three: OPTIONAL BOOLEAN R:0 D:1}}
{{two: OPTIONAL BINARY R:0 D:1}}
{{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
{{row group 1: RC:3 TS:211 OFFSET:4}}
{{--------------------------------------------------------------------------------}}
{{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
{{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
{{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
{{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
> [Python] writing version 2.0 parquet format with dictionary encoding enabled
> ----------------------------------------------------------------------------
>
> Key: ARROW-3564
> URL: https://issues.apache.org/jira/browse/ARROW-3564
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Python
> Affects Versions: 0.11.0
> Reporter: Hatem Helal
> Priority: Major
> Labels: parquet
> Fix For: 0.13.0
>
> Attachments: example_v1.0_dict_False.parquet,
> example_v1.0_dict_True.parquet, example_v2.0_dict_False.parquet,
> example_v2.0_dict_True.parquet, pyarrow_repro.py
>
>
> Using pyarrow v0.11.0, the following script writes a simple table (lifted
> from the [pyarrow doc|https://arrow.apache.org/docs/python/parquet.html]) to
> both parquet format versions 1.0 and 2.0, with and without dictionary
> encoding enabled.
>
>
> {{import}}{{ }}{{pyarrow.parquet as pq}}
> {{import}}{{ }}{{numpy as np}}
> {{import}}{{ }}{{pandas as pd}}
> {{import}}{{ }}{{pyarrow as pa}}
> {{import}}{{ }}{{itertools}}{{}}
> {{df }}{{=}} {{pd.DataFrame({}}{{'one'}}{{: [}}\{{-}}\{{1}}\{{, np.nan,
> }}\{{2.5}}{{],}}
> {{ }}{{'two'}}{{: [}}\{{'foo'}}\{{, }}\{{'bar'}}\{{, }}\{{'baz'}}{{],}}
> {{ }}{{'three'}}{{: [}}\{{True}}\{{, }}\{{False}}\{{, }}\{{True}}{{]},}}
> {{ }}{{index}}{{=}}{{list}}{{(}}{{'abc'}}{{))}}
>
> {{table }}{{=}} {{pa.Table.from_pandas(df)}}
>
> {{use_dict }}{{=}} {{[}}\\{{True}}\\{{, }}\\{{False}}{{]}}
> {{version }}{{=}} {{[}}\\{{'1.0'}}\\{{, }}\\{{'2.0'}}{{]}}
>
> {{for}} {{tf, v }}{{in}} {{itertools.product(use_dict, version):}}
> {{ }}{{filename }}{{=}} {{'example_v'}} +{{v}}+ {{'_dict_'}}
> +{{str}}{{(tf)}}+ {{'.parquet'}}
> {{ }}{{pq.write_table(table, filename, use_dictionary}}{{=}}{{tf,
> version}}{{=}}{{v)}}|
> Inspecting the written files using
> [parquet-tools|https://github.com/apache/parquet-mr/tree/master/parquet-tools]
> appears to show that dictionary encoding is not used in either of the
> version 2.0 files. Both files report that the columns are encoded using
> {{PLAIN,RLE}} and that the dictionary page offset is zero. I was expecting
> that the column encoding would include {{RLE_DICTIONARY}}. Attached are the
> script with repro steps and the files that were generated by it.
> Below is the output of using {{parquet-tools meta}} on the version 2.0 files
> {panel:title=version='2.0', use_dictionary = True}
> {panel}
> |{{% parquet-tools meta example_v2.0_dict_True.parquet}}
> {{file:
> [file:.../example_v2.0_dict_True.parquet|file:///.../example_v2.0_dict_True.parquet]}}
> {{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
> \{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
> ["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
> "name": "one", "numpy_type": "float64", "pandas_type": "float64"}
> , {"metadata": null, "field_name": "three", "name": "three", "numpy_type":
> "bool", "pandas_type": "bool"}
> , {"metadata": null, "field_name": "two", "name": "two", "numpy_type":
> "object", "pandas_type": "bytes"}
> , {"metadata": null, "field_name": "__index_level_0__", "name": null,
> "numpy_type": "object", "pandas_type": "bytes"}
> ], "column_indexes": [\\\{"metadata": null, "field_name": null, "name": null,
> "numpy_type": "object", "pandas_type": "bytes"}|file://%7B/]}}}
>
> {{file schema: schema}}
>
> {{--------------------------------------------------------------------------------}}
> {{one: OPTIONAL DOUBLE R:0 D:1}}
> {{three: OPTIONAL BOOLEAN R:0 D:1}}
> {{two: OPTIONAL BINARY R:0 D:1}}
> {{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
>
> {{row group 1: RC:3 TS:211 OFFSET:4}}
>
> {{--------------------------------------------------------------------------------}}
> {{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
> ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
> {{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
> ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
> {{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
> ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
> {{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
> ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
> {panel:title=version='2.0', use_dictionary = False}
> {panel}
> |{{% parquet-tools meta example_v2.0_dict_False.parquet}}
> {{file:
> [file:.../example_v2.0_dict_False.parquet|file:///.../example_v2.0_dict_False.parquet]}}
> {{creator: parquet-cpp version 1.5.1-SNAPSHOT}}
> \{{extra: pandas = {"pandas_version": "0.23.4", "index_columns":
> ["__index_level_0__"], "columns": [\{"metadata": null, "field_name": "one",
> "name": "one", "numpy_type": "float64", "pandas_type": "float64"}
> , {"metadata": null, "field_name": "three", "name": "three", "numpy_type":
> "bool", "pandas_type": "bool"}
> , {"metadata": null, "field_name": "two", "name": "two", "numpy_type":
> "object", "pandas_type": "bytes"}
> , {"metadata": null, "field_name": "__index_level_0__", "name": null,
> "numpy_type": "object", "pandas_type": "bytes"}
> ], "column_indexes": [\\\{"metadata": null, "field_name": null, "name": null,
> "numpy_type": "object", "pandas_type": "bytes"}|file://%7B/]}}}
>
> {{file schema: schema}}
>
> {{--------------------------------------------------------------------------------}}
> {{one: OPTIONAL DOUBLE R:0 D:1}}
> {{three: OPTIONAL BOOLEAN R:0 D:1}}
> {{two: OPTIONAL BINARY R:0 D:1}}
> {{__index_level_0__: OPTIONAL BINARY R:0 D:1}}
>
> {{row group 1: RC:3 TS:211 OFFSET:4}}
>
> {{--------------------------------------------------------------------------------}}
> {{one: DOUBLE SNAPPY DO:0 FPO:4 SZ:65/63/0.97 VC:3
> ENC:PLAIN,RLE ST:[min: -1.0, max: 2.5, num_nulls: 1]}}
> {{three: BOOLEAN SNAPPY DO:0 FPO:142 SZ:36/34/0.94 VC:3
> ENC:PLAIN,RLE ST:[min: false, max: true, num_nulls: 0]}}
> {{two: BINARY SNAPPY DO:0 FPO:225 SZ:60/58/0.97 VC:3
> ENC:PLAIN,RLE ST:[min: 0x626172, max: 0x666F6F, num_nulls: 0]}}
> {{__index_level_0__: BINARY SNAPPY DO:0 FPO:328 SZ:50/48/0.96 VC:3
> ENC:PLAIN,RLE ST:[min: 0x61, max: 0x63, num_nulls: 0]}}|
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