You are viewing a plain text version of this content. The canonical link for it is here.
Posted to github@datafusion.apache.org by "zhuqi-lucas (via GitHub)" <gi...@apache.org> on 2025/07/17 03:32:24 UTC
[PR] benchmark: Add parquet h2o support [datafusion]
zhuqi-lucas opened a new pull request, #16804:
URL: https://github.com/apache/datafusion/pull/16804
## Which issue does this PR close?
Currently, we only support for CSV format for h2o benchmark, but from the compare with other database result, it is using parquet, so this ticket try to support parquet format benchmark in datafusion.
Details:
https://github.com/apache/datafusion/issues/16710#issuecomment-3078052376
## Rationale for this change
Currently, we only support for CSV format for h2o benchmark, but from the compare with other database result, it is using parquet, so this ticket try to support parquet format benchmark in datafusion.
## What changes are included in this PR?
Currently, we only support for CSV format for h2o benchmark, but from the compare with other database result, it is using parquet, so this ticket try to support parquet format benchmark in datafusion.
## Are these changes tested?
Tested group by, join has some problem.
## Are there any user-facing changes?
Yes, new format support.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3082603389
Updated, it works now, the falsa has merged the fix and released: https://github.com/mrpowers-io/falsa/pull/28
```rust
./bench.sh data h2o_small_join_parquet
***************************
DataFusion Benchmark Runner and Data Generator
COMMAND: data
BENCHMARK: h2o_small_join_parquet
DATA_DIR: /Users/zhuqi/arrow-datafusion/benchmarks/data
CARGO_COMMAND: cargo run --release
PREFER_HASH_JOIN: true
***************************
Found Python version 3.13, which is suitable.
Using Python command: /opt/homebrew/bin/python3
Installing falsa...
Generating h2o test data in /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o with size=SMALL and format=PARQUET
10 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e7_1e1_0.parquet
10000 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e7_1e4_0.parquet
10000000 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e7_1e7_NA.parquet
An SMALL data schema is the following:
id1: int64 not null
id4: string not null
v2: double not null
An output format is PARQUET
Batch mode is supported.
In case of memory problems you can try to reduce a batch_size.
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
An MEDIUM data schema is the following:
id1: int64 not null
id2: int64 not null
id4: string not null
id5: string not null
v2: double not null
An output format is PARQUET
Batch mode is supported.
In case of memory problems you can try to reduce a batch_size.
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
An BIG data schema is the following:
id1: int64 not null
id2: int64 not null
id3: int64 not null
id4: string not null
id5: string not null
id6: string not null
v2: double not null
An output format is PARQUET
Batch mode is supported.
In case of memory problems you can try to reduce a batch_size.
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:02
An LSH data schema is the following:
id1: int64 not null
id2: int64 not null
id3: int64 not null
id4: string not null
id5: string not null
id6: string not null
v1: double not null
An output format is PARQUET
Batch mode is supported.
In case of memory problems you can try to reduce a batch_size.
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
```
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3083126587
> Thank you! it LGTM. I have also tested it locally.
Thank you @2010YOUY01 for review!
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3082332726
Updated: error for parquet join data generate, it works for group by:
```rust
./bench.sh data h2o_medium_join_parquet
***************************
DataFusion Benchmark Runner and Data Generator
COMMAND: data
BENCHMARK: h2o_medium_join_parquet
DATA_DIR: /Users/zhuqi/arrow-datafusion/benchmarks/data
CARGO_COMMAND: cargo run --release
PREFER_HASH_JOIN: true
***************************
Found Python version 3.13, which is suitable.
Using Python command: /opt/homebrew/bin/python3
Installing falsa...
Generating h2o test data in /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o with size=MEDIUM and format=PARQUET
100 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e2_0.parquet
100000 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e5_0.parquet
100000000 rows will be saved into: /Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e8_NA.parquet
An SMALL data schema is the following:
id1: int64 not null
id4: string
v2: double
An output format is PARQUET
Batch mode is supported.
In case of memory problems you can try to reduce a batch_size.
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0% -:--:--
╭──────────────────────────────────────────────────────────────────────────────────────── Traceback (most recent call last) ─────────────────────────────────────────────────────────────────────────────────────────╮
│ /Users/zhuqi/arrow-datafusion/benchmarks/venv/lib/python3.13/site-packages/falsa/app.py:144 in join │
│ │
│ 141 │ ) │
│ 142 │ │
│ 143 │ for batch in track(join_small.iter_batches(), total=len(join_small.batches)): │
│ ❱ 144 │ │ writer_small.write_batch(batch) │
│ 145 │ writer_small.close() │
│ 146 │ │
│ 147 │ if data_format is Format.DELTA: │
│ │
│ ╭──────────────────────────────────────────────────────────────────────────────────────────────────── locals ────────────────────────────────────────────────────────────────────────────────────────────────────╮ │
│ │ batch = pyarrow.RecordBatch │ │
│ │ id1: int64 not null │ │
│ │ id4: string not null │ │
│ │ v2: double not null │ │
│ │ ---- │ │
│ │ id1: [12,77,106,10,52,105,29,64,46,51,...,110,82,72,8,1,104,69,5,44,25] │ │
│ │ id4: ["id12","id77","id106","id10","id52","id105","id29","id64","id46","id51",...,"id110","id82","id72","id8","id1","id104","id69","id5","id44","id25"] │ │
│ │ v2: │ │
│ │ [53.0075954693085,32.410072200393316,72.68372205230826,71.61363809771296,86.99915627358179,15.539006557813716,23.840799451398684,7.23383214431385,6.366591524991982,20.222312628293857… │ │
│ │ batch_size = 5000000 │ │
│ │ data_filename_big = 'J1_1e8_1e8_NA.parquet' │ │
│ │ data_filename_lhs = 'J1_1e8_NA_0.parquet' │ │
│ │ data_filename_medium = 'J1_1e8_1e5_0.parquet' │ │
│ │ data_filename_small = 'J1_1e8_1e2_0.parquet' │ │
│ │ data_format = <Format.PARQUET: 'PARQUET'> │ │
│ │ generation_seed = 6839596180442651345 │ │
│ │ join_big = <falsa.local_fs.JoinBigGenerator object at 0x105e2fe00> │ │
│ │ join_lhs = <falsa.local_fs.JoinLHSGenerator object at 0x105e2da90> │ │
│ │ join_medium = <falsa.local_fs.JoinMediumGenerator object at 0x105e2fcb0> │ │
│ │ join_small = <falsa.local_fs.JoinSmallGenerator object at 0x105e2fb60> │ │
│ │ k = 10 │ │
│ │ keys_seed = 1026847926404610461 │ │
│ │ n_big = 100000000 │ │
│ │ n_medium = 100000 │ │
│ │ n_small = 100 │ │
│ │ nas = 0 │ │
│ │ output_big = PosixPath('/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e8_NA.parquet') │ │
│ │ output_dir = PosixPath('/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o') │ │
│ │ output_lhs = PosixPath('/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_NA_0.parquet') │ │
│ │ output_medium = PosixPath('/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e5_0.parquet') │ │
│ │ output_small = PosixPath('/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o/J1_1e8_1e2_0.parquet') │ │
│ │ path_prefix = '/Users/zhuqi/arrow-datafusion/benchmarks/data/h2o' │ │
│ │ seed = 42 │ │
│ │ size = <Size.MEDIUM: 'MEDIUM'> │ │
│ │ writer_small = <pyarrow.parquet.core.ParquetWriter object at 0x1067d4050> │ │
│ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │
│ │
│ /Users/zhuqi/arrow-datafusion/benchmarks/venv/lib/python3.13/site-packages/pyarrow/parquet/core.py:1089 in write_batch │
│ │
│ 1086 │ │ │ will be used instead. │
│ 1087 │ │ """ │
│ 1088 │ │ table = pa.Table.from_batches([batch], batch.schema) │
│ ❱ 1089 │ │ self.write_table(table, row_group_size) │
│ 1090 │ │
│ 1091 │ def write_table(self, table, row_group_size=None): │
│ 1092 │ │ """ │
│ │
│ ╭──────────────────────────────────────────────────────────────────────────────────────────────────── locals ────────────────────────────────────────────────────────────────────────────────────────────────────╮ │
│ │ batch = pyarrow.RecordBatch │ │
│ │ id1: int64 not null │ │
│ │ id4: string not null │ │
│ │ v2: double not null │ │
│ │ ---- │ │
│ │ id1: [12,77,106,10,52,105,29,64,46,51,...,110,82,72,8,1,104,69,5,44,25] │ │
│ │ id4: ["id12","id77","id106","id10","id52","id105","id29","id64","id46","id51",...,"id110","id82","id72","id8","id1","id104","id69","id5","id44","id25"] │ │
│ │ v2: │ │
│ │ [53.0075954693085,32.410072200393316,72.68372205230826,71.61363809771296,86.99915627358179,15.539006557813716,23.840799451398684,7.23383214431385,6.366591524991982,20.222312628293857,...,6… │ │
│ │ row_group_size = None │ │
│ │ self = <pyarrow.parquet.core.ParquetWriter object at 0x1067d4050> │ │
│ │ table = pyarrow.Table │ │
│ │ id1: int64 not null │ │
│ │ id4: string not null │ │
│ │ v2: double not null │ │
│ │ ---- │ │
│ │ id1: [[12,77,106,10,52,...,104,69,5,44,25]] │ │
│ │ id4: [["id12","id77","id106","id10","id52",...,"id104","id69","id5","id44","id25"]] │ │
│ │ v2: │ │
│ │ [[53.0075954693085,32.410072200393316,72.68372205230826,71.61363809771296,86.99915627358179,...,26.7118533955444,73.44416011403574,93.63022604514522,51.816253173876824,78.95727980955964]] │ │
│ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │
│ │
│ /Users/zhuqi/arrow-datafusion/benchmarks/venv/lib/python3.13/site-packages/pyarrow/parquet/core.py:1113 in write_table │
│ │
│ 1110 │ │ │ msg = ('Table schema does not match schema used to create file: ' │
│ 1111 │ │ │ │ '\ntable:\n{!s} vs. \nfile:\n{!s}' │
│ 1112 │ │ │ │ .format(table.schema, self.schema)) │
│ ❱ 1113 │ │ │ raise ValueError(msg) │
│ 1114 │ │ │
│ 1115 │ │ self.writer.write_table(table, row_group_size=row_group_size) │
│ 1116 │
│ │
│ ╭──────────────────────────────────────────────────────────────────────────────────────────────────── locals ────────────────────────────────────────────────────────────────────────────────────────────────────╮ │
│ │ msg = 'Table schema does not match schema used to create file: \ntable:\nid1: int64 not n'+98 │ │
│ │ row_group_size = None │ │
│ │ self = <pyarrow.parquet.core.ParquetWriter object at 0x1067d4050> │ │
│ │ table = pyarrow.Table │ │
│ │ id1: int64 not null │ │
│ │ id4: string not null │ │
│ │ v2: double not null │ │
│ │ ---- │ │
│ │ id1: [[12,77,106,10,52,...,104,69,5,44,25]] │ │
│ │ id4: [["id12","id77","id106","id10","id52",...,"id104","id69","id5","id44","id25"]] │ │
│ │ v2: │ │
│ │ [[53.0075954693085,32.410072200393316,72.68372205230826,71.61363809771296,86.99915627358179,...,26.7118533955444,73.44416011403574,93.63022604514522,51.816253173876824,78.95727980955964]] │ │
│ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Table schema does not match schema used to create file:
table:
id1: int64 not null
id4: string not null
v2: double not null vs.
file:
id1: int64 not null
id4: string
v2: double
```
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "2010YOUY01 (via GitHub)" <gi...@apache.org>.
2010YOUY01 commented on code in PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#discussion_r2212651111
##########
benchmarks/bench.sh:
##########
@@ -100,15 +100,24 @@ clickbench_pushdown: ClickBench queries against partitioned (100 files) parqu
clickbench_extended: ClickBench \"inspired\" queries against a single parquet (DataFusion specific)
# H2O.ai Benchmarks (Group By, Join, Window)
-h2o_small: h2oai benchmark with small dataset (1e7 rows) for groupby, default file format is csv
-h2o_medium: h2oai benchmark with medium dataset (1e8 rows) for groupby, default file format is csv
-h2o_big: h2oai benchmark with large dataset (1e9 rows) for groupby, default file format is csv
-h2o_small_join: h2oai benchmark with small dataset (1e7 rows) for join, default file format is csv
-h2o_medium_join: h2oai benchmark with medium dataset (1e8 rows) for join, default file format is csv
-h2o_big_join: h2oai benchmark with large dataset (1e9 rows) for join, default file format is csv
-h2o_small_window: Extended h2oai benchmark with small dataset (1e7 rows) for window, default file format is csv
-h2o_medium_window: Extended h2oai benchmark with medium dataset (1e8 rows) for window, default file format is csv
-h2o_big_window: Extended h2oai benchmark with large dataset (1e9 rows) for window, default file format is csv
+h2o_small: h2oai benchmark with small dataset (1e7 rows) for groupby, default file format is csv
Review Comment:
Later, we can clean it up with additional size/format options
like
`./bench.sh run h2o_join medium parquet`
##########
benchmarks/bench.sh:
##########
@@ -775,6 +840,7 @@ data_h2o() {
# Set virtual environment directory
VIRTUAL_ENV="${PWD}/venv"
+ rm -rf "$VIRTUAL_ENV"
Review Comment:
Could you add a comment for this line?
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on code in PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#discussion_r2212666921
##########
benchmarks/bench.sh:
##########
@@ -775,6 +840,7 @@ data_h2o() {
# Set virtual environment directory
VIRTUAL_ENV="${PWD}/venv"
+ rm -rf "$VIRTUAL_ENV"
Review Comment:
Thank you @2010YOUY01 , i removed this line in latest PR, i think this is tested code i added.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3082646775
> @zhuqi-lucas Just for the case falsa generates too much noise in stdout (and runner's output), I can add a command-line argument to suppress it. Something like `--silent`.
Thank you @SemyonSinchenko , it's ok for benchmark data generation, we can see the details info.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on code in PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#discussion_r2212668550
##########
benchmarks/bench.sh:
##########
@@ -100,15 +100,24 @@ clickbench_pushdown: ClickBench queries against partitioned (100 files) parqu
clickbench_extended: ClickBench \"inspired\" queries against a single parquet (DataFusion specific)
# H2O.ai Benchmarks (Group By, Join, Window)
-h2o_small: h2oai benchmark with small dataset (1e7 rows) for groupby, default file format is csv
-h2o_medium: h2oai benchmark with medium dataset (1e8 rows) for groupby, default file format is csv
-h2o_big: h2oai benchmark with large dataset (1e9 rows) for groupby, default file format is csv
-h2o_small_join: h2oai benchmark with small dataset (1e7 rows) for join, default file format is csv
-h2o_medium_join: h2oai benchmark with medium dataset (1e8 rows) for join, default file format is csv
-h2o_big_join: h2oai benchmark with large dataset (1e9 rows) for join, default file format is csv
-h2o_small_window: Extended h2oai benchmark with small dataset (1e7 rows) for window, default file format is csv
-h2o_medium_window: Extended h2oai benchmark with medium dataset (1e8 rows) for window, default file format is csv
-h2o_big_window: Extended h2oai benchmark with large dataset (1e9 rows) for window, default file format is csv
+h2o_small: h2oai benchmark with small dataset (1e7 rows) for groupby, default file format is csv
Review Comment:
Good suggestion @2010YOUY01 , it's more clear.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3082341745
Create the jira for falsa side, it fails with generate parquet data for join set, but it works well with group by.
https://github.com/mrpowers-io/falsa/issues/27
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "SemyonSinchenko (via GitHub)" <gi...@apache.org>.
SemyonSinchenko commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3082635479
@zhuqi-lucas Just for the case falsa generates too much noise in stdout (and runner's output), I can add a command-line argument to suppress it. Something like `--silent`.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "zhuqi-lucas (via GitHub)" <gi...@apache.org>.
zhuqi-lucas commented on PR #16804:
URL: https://github.com/apache/datafusion/pull/16804#issuecomment-3086556019
Thank you @alamb @jonathanc-n for review.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org
Re: [PR] benchmark: Add parquet h2o support [datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb merged PR #16804:
URL: https://github.com/apache/datafusion/pull/16804
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscribe@datafusion.apache.org
For additional commands, e-mail: github-help@datafusion.apache.org