-
Notifications
You must be signed in to change notification settings - Fork 20
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
add better cost model with rowcnt, network and io cost #13
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Signed-off-by: Alex Chi <iskyzh@gmail.com>
Gun9niR
added a commit
that referenced
this pull request
Mar 20, 2024
Generate the statistics in perftest and put them into `BaseCostModel` in `DatafusionOptimizer`. Below is the comparison before & after stats are added. You can check `PhysicalScan`, where the cost has changed. The final cardinality remains the same because when stats on a column is missing, we use a very small magic number `INVALID_SELECTIVITY` (0.001) that just sets cardinality to 1. ### Todos in Future PRs - Support generating stats on `Utf8`. - Set a better magic number. - Generate MCV. ### Before ``` plan space size budget used, not applying logical rules any more. current plan space: 1094 explain: PhysicalSort ├── exprs:SortOrder { order: Desc } │ └── #1 ├── cost: weighted=185.17,row_cnt=1.00,compute=179.17,io=6.00 └── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=182.12,row_cnt=1.00,compute=176.12,io=6.00 } └── PhysicalAgg ├── aggrs:Agg(Sum) │ └── Mul │ ├── #0 │ └── Sub │ ├── 1 │ └── #1 ├── groups: [ #2 ] ├── cost: weighted=182.02,row_cnt=1.00,compute=176.02,io=6.00 └── PhysicalProjection { exprs: [ #0, #1, #2 ], cost: weighted=64.90,row_cnt=1.00,compute=58.90,io=6.00 } └── PhysicalProjection { exprs: [ #0, #1, #4, #5, #6 ], cost: weighted=64.76,row_cnt=1.00,compute=58.76,io=6.00 } └── PhysicalProjection { exprs: [ #2, #3, #5, #6, #7, #8, #9 ], cost: weighted=64.54,row_cnt=1.00,compute=58.54,io=6.00 } └── PhysicalProjection { exprs: [ #0, #3, #4, #5, #6, #7, #8, #9, #10, #11 ], cost: weighted=64.24,row_cnt=1.00,compute=58.24,io=6.00 } └── PhysicalProjection { exprs: [ #1, #2, #4, #5, #6, #7, #8, #9, #10, #11, #12, #13 ], cost: weighted=63.82,row_cnt=1.00,compute=57.82,io=6.00 } └── PhysicalProjection { exprs: [ #0, #3, #8, #9, #10, #11, #12, #13, #14, #15, #16, #17, #18, #19 ], cost: weighted=63.32,row_cnt=1.00,compute=57.32,io=6.00 } └── PhysicalNestedLoopJoin ├── join_type: Inner ├── cond:And │ ├── Eq │ │ ├── #11 │ │ └── #14 │ └── Eq │ ├── #3 │ └── #15 ├── cost: weighted=62.74,row_cnt=1.00,compute=56.74,io=6.00 ├── PhysicalHashJoin { join_type: Inner, left_keys: [ #0 ], right_keys: [ #1 ], cost: weighted=35.70,row_cnt=1.00,compute=32.70,io=3.00 } │ ├── PhysicalScan { table: customer, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } │ └── PhysicalHashJoin { join_type: Inner, left_keys: [ #0 ], right_keys: [ #0 ], cost: weighted=31.64,row_cnt=1.00,compute=29.64,io=2.00 } │ ├── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=27.40,row_cnt=1.00,compute=26.40,io=1.00 } │ │ └── PhysicalFilter │ │ ├── cond:And │ │ │ ├── Geq │ │ │ │ ├── #2 │ │ │ │ └── 9131 │ │ │ └── Lt │ │ │ ├── #2 │ │ │ └── 9496 │ │ ├── cost: weighted=27.30,row_cnt=1.00,compute=26.30,io=1.00 │ │ └── PhysicalProjection { exprs: [ #0, #1, #4 ], cost: weighted=1.14,row_cnt=1.00,compute=0.14,io=1.00 } │ │ └── PhysicalScan { table: orders, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } │ └── PhysicalProjection { exprs: [ #0, #2, #5, #6 ], cost: weighted=1.18,row_cnt=1.00,compute=0.18,io=1.00 } │ └── PhysicalScan { table: lineitem, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } └── PhysicalProjection { exprs: [ #0, #3, #7, #8, #9, #10 ], cost: weighted=15.72,row_cnt=1.00,compute=12.72,io=3.00 } └── PhysicalHashJoin { join_type: Inner, left_keys: [ #3 ], right_keys: [ #0 ], cost: weighted=15.46,row_cnt=1.00,compute=12.46,io=3.00 } ├── PhysicalScan { table: supplier, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } └── PhysicalHashJoin { join_type: Inner, left_keys: [ #2 ], right_keys: [ #0 ], cost: weighted=11.40,row_cnt=1.00,compute=9.40,io=2.00 } ├── PhysicalProjection { exprs: [ #0, #1, #2 ], cost: weighted=1.14,row_cnt=1.00,compute=0.14,io=1.00 } │ └── PhysicalScan { table: nation, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } └── PhysicalProjection { exprs: [ #0 ], cost: weighted=7.20,row_cnt=1.00,compute=6.20,io=1.00 } └── PhysicalFilter ├── cond:Eq │ ├── #1 │ └── "AMERICA" ├── cost: weighted=7.14,row_cnt=1.00,compute=6.14,io=1.00 └── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=1.10,row_cnt=1.00,compute=0.10,io=1.00 } └── PhysicalScan { table: region, cost: weighted=1.00,row_cnt=1.00,compute=0.00,io=1.00 } plan space size budget used, not applying logical rules any more. current plan space: 1094 qerrors: {"DataFusion": [5.0]} ``` ### After ``` plan space size budget used, not applying logical rules any more. current plan space: 1094 explain: PhysicalSort ├── exprs:SortOrder { order: Desc } │ └── #1 ├── cost: weighted=336032.32,row_cnt=1.00,compute=259227.32,io=76805.00 └── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=336029.27,row_cnt=1.00,compute=259224.27,io=76805.00 } └── PhysicalAgg ├── aggrs:Agg(Sum) │ └── Mul │ ├── #0 │ └── Sub │ ├── 1 │ └── #1 ├── groups: [ #2 ] ├── cost: weighted=336029.17,row_cnt=1.00,compute=259224.17,io=76805.00 └── PhysicalProjection { exprs: [ #0, #1, #2 ], cost: weighted=335912.05,row_cnt=1.00,compute=259107.05,io=76805.00 } └── PhysicalProjection { exprs: [ #0, #1, #4, #5, #6 ], cost: weighted=335911.91,row_cnt=1.00,compute=259106.91,io=76805.00 } └── PhysicalProjection { exprs: [ #2, #3, #5, #6, #7, #8, #9 ], cost: weighted=335911.69,row_cnt=1.00,compute=259106.69,io=76805.00 } └── PhysicalProjection { exprs: [ #0, #3, #4, #5, #6, #7, #8, #9, #10, #11 ], cost: weighted=335911.39,row_cnt=1.00,compute=259106.39,io=76805.00 } └── PhysicalProjection { exprs: [ #1, #2, #4, #5, #6, #7, #8, #9, #10, #11, #12, #13 ], cost: weighted=335910.97,row_cnt=1.00,compute=259105.97,io=76805.00 } └── PhysicalProjection { exprs: [ #0, #3, #8, #9, #10, #11, #12, #13, #14, #15, #16, #17, #18, #19 ], cost: weighted=335910.47,row_cnt=1.00,compute=259105.47,io=76805.00 } └── PhysicalNestedLoopJoin ├── join_type: Inner ├── cond:And │ ├── Eq │ │ ├── #11 │ │ └── #14 │ └── Eq │ ├── #3 │ └── #15 ├── cost: weighted=335909.89,row_cnt=1.00,compute=259104.89,io=76805.00 ├── PhysicalProjection { exprs: [ #6, #7, #8, #9, #10, #11, #12, #13, #0, #1, #2, #3, #4, #5 ], cost: weighted=335619.21,row_cnt=1.00,compute=258944.21,io=76675.00 } │ └── PhysicalHashJoin { join_type: Inner, left_keys: [ #1 ], right_keys: [ #0 ], cost: weighted=335618.63,row_cnt=1.00,compute=258943.63,io=76675.00 } │ ├── PhysicalProjection { exprs: [ #4, #5, #0, #1, #2, #3 ], cost: weighted=332616.57,row_cnt=1.00,compute=257441.57,io=75175.00 } │ │ └── PhysicalProjection { exprs: [ #0, #2, #5, #6, #16, #17 ], cost: weighted=332616.31,row_cnt=1.00,compute=257441.31,io=75175.00 } │ │ └── PhysicalProjection { exprs: [ #2, #3, #4, #5, #6, #7, #8, #9, #10, #11, #12, #13, #14, #15, #16, #17, #0, #1 ], cost: weighted=332616.05,row_cnt=1.00,compute=257441.05,io=75175.00 } │ │ └── PhysicalHashJoin { join_type: Inner, left_keys: [ #0 ], right_keys: [ #0 ], cost: weighted=332615.31,row_cnt=1.00,compute=257440.31,io=75175.00 } │ │ ├── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=212263.25,row_cnt=1.00,compute=197263.25,io=15000.00 } │ │ │ └── PhysicalFilter │ │ │ ├── cond:And │ │ │ │ ├── Geq │ │ │ │ │ ├── #2 │ │ │ │ │ └── 9131 │ │ │ │ └── Lt │ │ │ │ ├── #2 │ │ │ │ └── 9496 │ │ │ ├── cost: weighted=212263.15,row_cnt=1.00,compute=197263.15,io=15000.00 │ │ │ └── PhysicalProjection { exprs: [ #0, #1, #4 ], cost: weighted=16050.07,row_cnt=15000.00,compute=1050.07,io=15000.00 } │ │ │ └── PhysicalScan { table: orders, cost: weighted=15000.00,row_cnt=15000.00,compute=0.00,io=15000.00 } │ │ └── PhysicalScan { table: lineitem, cost: weighted=60175.00,row_cnt=60175.00,compute=0.00,io=60175.00 } │ └── PhysicalScan { table: customer, cost: weighted=1500.00,row_cnt=1500.00,compute=0.00,io=1500.00 } └── PhysicalProjection { exprs: [ #0, #3, #7, #8, #9, #10 ], cost: weighted=279.36,row_cnt=1.00,compute=149.36,io=130.00 } └── PhysicalProjection { exprs: [ #4, #5, #6, #7, #8, #9, #10, #0, #1, #2, #3 ], cost: weighted=279.10,row_cnt=1.00,compute=149.10,io=130.00 } └── PhysicalProjection { exprs: [ #1, #2, #3, #0, #4, #5, #6, #7, #8, #9, #10 ], cost: weighted=278.64,row_cnt=1.00,compute=148.64,io=130.00 } └── PhysicalHashJoin { join_type: Inner, left_keys: [ #1 ], right_keys: [ #3 ], cost: weighted=278.18,row_cnt=1.00,compute=148.18,io=130.00 } ├── PhysicalProjection { exprs: [ #3, #0, #1, #2 ], cost: weighted=76.12,row_cnt=1.00,compute=46.12,io=30.00 } │ └── PhysicalProjection { exprs: [ #0, #1, #2, #4 ], cost: weighted=75.94,row_cnt=1.00,compute=45.94,io=30.00 } │ └── PhysicalProjection { exprs: [ #1, #2, #3, #4, #0 ], cost: weighted=75.76,row_cnt=1.00,compute=45.76,io=30.00 } │ └── PhysicalHashJoin { join_type: Inner, left_keys: [ #0 ], right_keys: [ #2 ], cost: weighted=75.54,row_cnt=1.00,compute=45.54,io=30.00 } │ ├── PhysicalProjection { exprs: [ #0 ], cost: weighted=23.48,row_cnt=1.00,compute=18.48,io=5.00 } │ │ └── PhysicalFilter │ │ ├── cond:Eq │ │ │ ├── #1 │ │ │ └── "AMERICA" │ │ ├── cost: weighted=23.42,row_cnt=1.00,compute=18.42,io=5.00 │ │ └── PhysicalProjection { exprs: [ #0, #1 ], cost: weighted=5.30,row_cnt=5.00,compute=0.30,io=5.00 } │ │ └── PhysicalScan { table: region, cost: weighted=5.00,row_cnt=5.00,compute=0.00,io=5.00 } │ └── PhysicalScan { table: nation, cost: weighted=25.00,row_cnt=25.00,compute=0.00,io=25.00 } └── PhysicalScan { table: supplier, cost: weighted=100.00,row_cnt=100.00,compute=0.00,io=100.00 } plan space size budget used, not applying logical rules any more. current plan space: 1094 qerrors: {"DataFusion": [5.0]} ```
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
cost model is now represented in
Vec<f64>
, whereas the first value is weighted cost.close #3