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Merge pull request #127 from jychen7/datafusion-7108
Datafusion v28
2 parents a8b0653 + 92689ce commit 643abc3

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datafusion/README.md

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@@ -4,24 +4,18 @@ DataFusion is an extensible query execution framework, written in Rust, that use
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We use parquet file here and create an external table for it; and then do the queries.
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## Generate benchmark results
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### To solve
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q32 (line 33 in queries.sql) out of memory in my 32GB memory vm, it output null now since it's killed
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### to generate benchmark results
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The benchmark should be completed in under an hour. On-demand pricing is $0.6 per hour while spot pricing is only $0.2 per hour.
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The benchmark should be completed in under an hour. On-demand pricing is $0.6 per hour while spot pricing is only $0.2 to $0.3 per hour (us-east-2).
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1. manually start a AWS EC2 instance
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- `c6a.4xlarge`
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- Amazon Linux 2 AMI
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- Root 500GB gp2 SSD
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- no EBS optimized
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- no instance store
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1. wait for status check passed, then ssh to EC2
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1. `sudo yum update -y` and `sudo yum install gcc -y`
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1. wait for status check passed, then ssh to EC2 `ssh ec2-user@{ip}`
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1. `sudo yum update -y` and `sudo yum install gcc git -y`
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1. `git clone https://github.com/ClickHouse/ClickBench`
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1. `cd ClickBench/datafusion`
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1. `vi benchmark.sh` and modify following line to target Datafusion version
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3. `comparing binary with utf-8` and `group by binary` don't work in mac, if you run these quries in mac, you'll get some errors for quries contain binary format apache/arrow-datafusion#3050
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### to generate full human readable results (for debugging)
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## Generate full human readable results (for debugging)
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1. install datafusion-cli
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2. download the parquet ```wget --no-verbose --continue https://datasets.clickhouse.com/hits_compatible/hits.parquet```

datafusion/results/single.json

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{
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"system": "DataFusion (single parquet)",
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"date": "2023-04-11",
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"system": "DataFusion (Parquet, single)",
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"date": "2023-07-29",
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"machine": "c6a.4xlarge, 500gb gp2",
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"cluster_size": 1,
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"comment": "v22.0.0 (34c9bce)",
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"comment": "v28.0.0 (51b4392)",
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"tags": ["Rust", "column-oriented", "embedded", "stateless"],
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"load_time": 0,
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"data_size": 14779976446,
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"result": [
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[2.646, 0.225, 0.226],
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[0.099, 0.079, 0.079],
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[0.173, 0.138, 0.139],
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[0.349, 0.126, 0.125],
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[2.790, 6.718, 2.717],
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[1.911, 1.753, 1.770],
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[0.090, 0.079, 0.076],
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[0.106, 0.081, 0.081],
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[3.032, 3.054, 3.675],
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[3.634, 3.564, 3.647],
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[0.508, 0.397, 0.402],
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[0.529, 0.424, 0.423],
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[2.100, 2.057, 2.040],
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[4.415, 4.169, 3.707],
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[2.198, 2.143, 2.080],
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[4.043, 3.516, 5.126],
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[5.065, 6.106, 8.249],
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[4.524, 4.420, 4.347],
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[10.981, 11.070, 11.203],
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[0.348, 0.112, 0.116],
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[9.968, 1.594, 1.619],
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[11.178, 1.917, 1.900],
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[22.120, 4.337, 4.352],
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[56.098, 12.159, 12.128],
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[2.581, 0.582, 0.583],
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[0.756, 0.478, 0.475],
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[2.556, 0.604, 0.570],
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[9.592, 2.525, 2.479],
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[9.067, 5.925, 5.927],
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[0.638, 0.563, 0.585],
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[3.278, 3.119, 2.940],
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[7.710, 4.401, 4.398],
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[null, null, null],
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[12.566, 8.695, 8.954],
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[12.827, 9.199, 11.148],
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[3.623, 3.514, 3.526],
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[0.506, 0.413, 0.406],
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[0.245, 0.217, 0.214],
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[0.249, 0.194, 0.194],
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[0.892, 0.772, 0.774],
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[0.175, 0.107, 0.106],
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[0.116, 0.095, 0.093],
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[0.142, 0.112, 0.117]
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[2.641, 0.232, 0.216],
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[0.092, 0.074, 0.073],
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[0.159, 0.121, 0.117],
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[0.351, 0.122, 0.120],
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[1.142, 0.874, 0.869],
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[1.399, 1.303, 1.329],
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[0.096, 0.075, 0.076],
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[0.094, 0.074, 0.076],
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[1.516, 1.481, 1.475],
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[2.711, 2.582, 2.583],
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[0.429, 0.332, 0.327],
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[0.558, 0.357, 0.360],
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[1.374, 1.323, 1.336],
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[3.559, 2.670, 2.733],
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[1.519, 1.487, 1.477],
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[1.041, 0.981, 0.988],
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[3.248, 2.748, 2.801],
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[3.139, 2.696, 2.688],
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[7.014, 5.770, 5.775],
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[0.271, 0.111, 0.109],
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[9.975, 1.558, 1.578],
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[11.163, 1.926, 1.881],
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[22.053, 4.208, 4.194],
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[56.007, 12.132, 12.113],
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[2.559, 0.602, 0.586],
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[0.737, 0.479, 0.489],
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[2.548, 0.589, 0.589],
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[9.550, 2.299, 2.286],
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[9.076, 5.399, 5.388],
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[0.579, 0.568, 0.584],
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[2.214, 1.136, 1.136],
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[5.734, 1.593, 1.598],
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[8.357, 7.896, 8.053],
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[11.556, 7.358, 7.369],
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[12.051, 7.878, 7.956],
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[1.866, 1.820, 1.807],
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[0.448, 0.347, 0.358],
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[0.231, 0.197, 0.195],
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[0.248, 0.198, 0.188],
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[0.843, 0.725, 0.722],
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[0.138, 0.091, 0.095],
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[0.115, 0.089, 0.088],
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[0.124, 0.097, 0.092]
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]
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}

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