feat: Parallel Arrow file format reading #8897
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alamb
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Jan 25, 2024
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The code looks good to me @my-vegetable-has-exploded -- thank you very much.
I think it is likely to not work well on remote object store given how many requests are made but I also think that could be handled by a follow on PR
My only concern with this PR as written is if the tests actually exercise the multi-batch reading code given how small the input files in repartition.slt are
| @@ -61,6 +61,7 @@ postgres = ["bytes", "chrono", "tokio-postgres", "postgres-types", "postgres-pro | |||
| [dev-dependencies] | |||
| env_logger = { workspace = true } | |||
| num_cpus = { workspace = true } | |||
| tokio = { version = "1.0", features = ["rt-multi-thread"] } | |||
| @@ -253,7 +253,16 @@ query TT | |||
| EXPLAIN SELECT * FROM arrow_table | |||
| ---- | |||
| logical_plan TableScan: arrow_table projection=[f0, f1, f2] | |||
| physical_plan ArrowExec: file_groups={1 group: [[WORKSPACE_ROOT/datafusion/core/tests/data/example.arrow]]}, projection=[f0, f1, f2] | |||
| physical_plan ArrowExec: file_groups={4 groups: [[WORKSPACE_ROOT/datafusion/core/tests/data/example.arrow:0..461], [WORKSPACE_ROOT/datafusion/core/tests/data/example.arrow:461..922], [WORKSPACE_ROOT/datafusion/core/tests/data/example.arrow:922..1383], [WORKSPACE_ROOT/datafusion/core/tests/data/example.arrow:1383..1842]]}, projection=[f0, f1, f2] | |||
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👍 looks good to me -- though I I wonder will this actually read in parallel (or do these ranges all end up in the same reader)?
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Which issue does this PR close?
Closes #8503
Rationale for this change
What changes are included in this PR?
If file_meta.range is some, filter recordbatches according to range, then scan recordbatches.
Are these changes tested?
physical plan of scaning arrow files changes in
repartition_scan.slt.Are there any user-facing changes?