Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-16 05:29 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.246 s 0.255
2023-01-16 05:34 Python dataframe-to-table type_strings 0.425 s 1.142
2023-01-16 05:31 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.113 s 0.285
2023-01-16 05:35 Python dataset-filter nyctaxi_2010-01 1.029 s -0.270
2023-01-16 05:43 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 84.355 s -0.798
2023-01-16 05:32 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.537 s 1.020
2023-01-16 05:39 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 80.788 s 0.048
2023-01-16 05:30 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.086 s -1.143
2023-01-16 05:31 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.434 s 0.531
2023-01-16 05:29 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.790 s -0.398
2023-01-16 05:34 Python dataframe-to-table chi_traffic_2020_Q1 21.224 s -0.680
2023-01-16 05:56 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.758 s 0.924
2023-01-16 06:25 Python file-read lz4, feather, table, nyctaxi_2010-01 0.666 s 0.406
2023-01-16 06:28 Python file-write uncompressed, feather, table, fanniemae_2016Q4 4.529 s 3.277
2023-01-16 05:35 Python dataframe-to-table type_nested 2.981 s -0.413
2023-01-16 05:55 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.190 s 0.152
2023-01-16 05:55 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.163 s 0.069
2023-01-16 05:56 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.305 s -0.715
2023-01-16 05:56 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.932 s -1.668
2023-01-16 05:56 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.538
2023-01-16 06:01 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.152 s -0.626
2023-01-16 06:08 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.050 s 0.908
2023-01-16 06:09 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.226 s -1.821
2023-01-16 06:28 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.415 s -1.238
2023-01-16 05:55 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.216 s 0.730
2023-01-16 05:55 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.294 s 0.298
2023-01-16 05:55 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.029 s 0.301
2023-01-16 06:13 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.902 s -1.701
2023-01-16 06:29 Python file-write lz4, feather, table, fanniemae_2016Q4 1.539 s 3.083
2023-01-16 06:31 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.501 s 1.472
2023-01-16 05:31 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.059 s -1.147
2023-01-16 05:55 Python dataset-read async=True, nyctaxi_multi_ipc_s3 224.363 s -0.366
2023-01-16 05:55 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.246 s 0.012
2023-01-16 05:56 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.114
2023-01-16 05:56 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.280
2023-01-16 06:09 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.866 s 1.066
2023-01-16 06:10 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.693 s 1.036
2023-01-16 05:33 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.472 s 1.015
2023-01-16 05:35 Python dataframe-to-table type_dict 0.011 s -0.226
2023-01-16 05:56 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.207 s -0.140
2023-01-16 05:57 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.534 s 0.869
2023-01-16 06:00 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.310 s -1.752
2023-01-16 06:09 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.233
2023-01-16 06:23 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.492 s 0.336
2023-01-16 06:24 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.621 s 0.352
2023-01-16 06:30 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.558 s 3.097
2023-01-16 06:30 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.581 s 1.556
2023-01-16 05:35 Python dataframe-to-table type_integers 0.010 s 0.682
2023-01-16 06:25 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.335 s 0.312
2023-01-16 05:35 Python dataframe-to-table type_floats 0.010 s 0.260
2023-01-16 06:09 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.046 s -1.594
2023-01-16 06:14 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.408 s 0.446
2023-01-16 06:23 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.615 s 0.357
2023-01-16 06:25 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.476 s 0.096
2023-01-16 06:00 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.151 s -0.861
2023-01-16 06:09 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.287 s -1.446
2023-01-16 06:09 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.963
2023-01-16 06:23 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.270 s 1.138
2023-01-16 06:23 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.627 s 0.434
2023-01-16 06:23 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.494 s 0.335
2023-01-16 06:24 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.964 s 0.303
2023-01-16 06:24 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.901 s 0.500
2023-01-16 06:29 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 13.516 s 3.343
2023-01-16 06:30 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.088 s 1.442
2023-01-16 05:55 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.401 s -0.527
2023-01-16 05:55 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.660 s 0.282
2023-01-16 06:24 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.972 s 0.179
2023-01-16 05:56 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.130 s 0.197
2023-01-16 05:56 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.198
2023-01-16 06:09 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.026 s -0.309
2023-01-16 06:14 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.410 s -1.059
2023-01-16 06:23 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.324 s 0.334
2023-01-16 06:24 Python file-read lz4, feather, table, fanniemae_2016Q4 0.822 s 0.125
2023-01-16 06:24 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.221 s 0.190
2023-01-16 06:24 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.933 s 0.125
2023-01-16 06:24 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.930 s 0.372
2023-01-16 06:25 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.589 s 0.333
2023-01-16 06:26 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.020 s -0.020
2023-01-16 06:27 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.839 s -1.120
2023-01-16 06:32 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 2.774 s 3.666
2023-01-16 06:31 Python file-write uncompressed, feather, table, nyctaxi_2010-01 1.944 s 3.507
2023-01-16 06:31 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 8.997 s 1.432
2023-01-16 06:32 Python file-write lz4, feather, table, nyctaxi_2010-01 1.374 s 3.561
2023-01-16 06:32 Python wide-dataframe use_legacy_dataset=false 0.507 s 0.998
2023-01-16 06:32 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 3.349 s 3.705
2023-01-16 06:32 Python wide-dataframe use_legacy_dataset=true 0.375 s 0.378
2023-01-16 06:57 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.716 s -1.180
2023-01-16 06:40 R dataframe-to-table chi_traffic_2020_Q1, R 4.386 s -1.633
2023-01-16 06:41 R dataframe-to-table type_dict, R 0.048 s 0.985
2023-01-16 06:41 R dataframe-to-table type_strings, R 0.535 s -0.164
2023-01-16 06:41 R dataframe-to-table type_floats, R 0.013 s 0.612
2023-01-16 06:41 R dataframe-to-table type_integers, R 0.010 s 0.620
2023-01-16 06:41 R dataframe-to-table type_nested, R 0.574 s -0.203
2023-01-16 06:42 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.321 s -0.086
2023-01-16 06:42 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.328 s -0.311
2023-01-16 06:43 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.567 s 0.285
2023-01-16 06:42 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.581 s -0.322
2023-01-16 06:42 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.574 s -0.101
2023-01-16 06:42 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.312 s 0.266
2023-01-16 06:43 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.601 s 0.279
2023-01-16 06:43 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.852 s 0.262
2023-01-16 06:43 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.910 s -0.024
2023-01-16 06:44 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.918 s -0.214
2023-01-16 06:43 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.573 s -0.340
2023-01-16 06:43 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.569 s -0.178
2023-01-16 06:44 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.217 s 0.317
2023-01-16 06:44 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.593 s 0.262
2023-01-16 06:44 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.820 s 0.314
2023-01-16 06:44 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.904 s 0.285
2023-01-16 06:45 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.858 s -1.482
2023-01-16 06:47 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.827 s -1.473
2023-01-16 06:48 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.267 s -1.441
2023-01-16 06:50 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.233 s -1.164
2023-01-16 06:51 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.967 s -1.118
2023-01-16 06:52 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.032 s 0.232
2023-01-16 06:53 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.495 s -0.671
2023-01-16 06:54 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.444 s 1.153
2023-01-16 06:55 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.983 s -1.160
2023-01-16 06:56 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.794 s -0.984
2023-01-16 06:58 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.751 s -1.066
2023-01-16 06:59 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.312 s -0.825
2023-01-16 07:00 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.175 s -0.336
2023-01-16 07:01 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.468 s 1.140
2023-01-16 07:02 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.079 s -0.528
2023-01-16 07:02 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.614 s -1.316
2023-01-16 07:02 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.544 s 0.899
2023-01-16 07:02 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.603 s -0.189
2023-01-16 07:03 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.282 s 0.190
2023-01-16 07:02 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.251 s 0.267
2023-01-16 07:03 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.200 s 0.270
2023-01-16 07:02 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.200 s 0.225
2023-01-16 07:03 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.240 s 0.239
2023-01-16 07:03 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.589 s -0.128
2023-01-16 07:03 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.279 s -0.375
2023-01-16 07:04 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.001 s 0.372
2023-01-16 07:04 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.723 s 0.409
2023-01-16 07:05 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.334 s 0.270
2023-01-16 07:04 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.291 s 0.070
2023-01-16 07:04 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -0.160
2023-01-16 07:04 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.088
2023-01-16 07:05 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.431 s 0.268
2023-01-16 07:05 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.349 s 0.151
2023-01-16 07:05 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.670 s -1.486
2023-01-16 07:05 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.185
2023-01-16 07:06 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.302 s 0.055
2023-01-16 07:05 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.061 s -0.488
2023-01-16 07:06 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.233 s 0.209
2023-01-16 07:06 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.270 s 0.162
2023-01-16 07:07 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.346
2023-01-16 07:06 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.303 s 0.261
2023-01-16 07:06 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.588 s 0.096
2023-01-16 07:07 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.900 s -0.048
2023-01-16 07:07 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.525 s -0.045
2023-01-16 07:08 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.272 s 0.148
2023-01-16 07:08 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.243 s 0.291
2023-01-16 07:07 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.203 s 0.192
2023-01-16 07:08 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.328 s 0.374
2023-01-16 07:07 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.238 s 0.134
2023-01-16 07:08 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.923 s -0.257
2023-01-16 07:09 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.193 s 0.042
2023-01-16 07:09 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.210
2023-01-16 07:09 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.314 s 0.206
2023-01-16 07:09 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.351 s 0.210
2023-01-16 07:09 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.267 s 0.145
2023-01-16 07:09 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.322 s 0.151
2023-01-16 07:09 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.637 s 0.178
2023-01-16 07:10 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.633 s 0.070
2023-01-16 07:10 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.174
2023-01-16 07:11 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.202 s 0.242
2023-01-16 07:11 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.160 s 0.269
2023-01-16 07:10 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.765 s -0.946
2023-01-16 07:11 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.178 s 0.331
2023-01-16 07:11 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.360
2023-01-16 07:11 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.509 s 0.172
2023-01-16 07:11 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.354 s 0.203
2023-01-16 07:12 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.264 s -0.077
2023-01-16 07:12 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.292 s 0.340
2023-01-16 07:12 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.339 s 0.386
2023-01-16 07:12 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.341
2023-01-16 07:13 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.658 s 0.253
2023-01-16 07:12 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.374 s 0.317
2023-01-16 07:13 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.350 s 0.307
2023-01-16 07:14 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.340 s 0.242
2023-01-16 07:13 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.787 s 0.065
2023-01-16 07:13 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.636 s -0.150
2023-01-16 07:14 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.333 s 0.318
2023-01-16 07:14 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.428 s 0.255
2023-01-16 07:14 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.369 s 0.245
2023-01-16 07:15 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.810 s -0.368
2023-01-16 07:17 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.974 s -0.916
2023-01-16 07:17 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.168 s -0.352
2023-01-16 07:16 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.371 s 0.326
2023-01-16 07:22 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.694 s -2.656
2023-01-16 07:14 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.394 s 0.323
2023-01-16 07:15 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.613 s 0.304
2023-01-16 07:16 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.296 s 0.329
2023-01-16 07:17 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.298 s 0.309
2023-01-16 07:18 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.879 s -0.150
2023-01-16 07:14 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.711 s 0.314
2023-01-16 07:17 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.255 s 0.226
2023-01-16 07:16 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.769 s 0.268
2023-01-16 07:19 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.304 s 0.230
2023-01-16 07:20 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.874 s -0.418
2023-01-16 07:15 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.271 s 0.342
2023-01-16 07:16 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.442 s 0.156
2023-01-16 07:17 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.259 s 0.254
2023-01-16 07:21 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.366 s 0.048
2023-01-16 07:21 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.497 s -1.589
2023-01-16 07:18 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.336 s 0.267
2023-01-16 07:18 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.322 s 0.176
2023-01-16 07:19 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.231 s 0.186
2023-01-16 07:20 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s 0.165
2023-01-16 07:18 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.652 s 0.154
2023-01-16 07:20 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.263 s -0.752
2023-01-16 07:20 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.257 s 0.058
2023-01-16 07:20 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.304 s -0.190
2023-01-16 07:16 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.323 s 0.351
2023-01-16 07:19 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.228
2023-01-16 07:20 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.542 s -0.063
2023-01-16 07:19 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.758 s -0.232
2023-01-16 07:22 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.614 s -0.934
2023-01-16 07:19 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.210 s 0.189
2023-01-16 07:19 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.329 s 0.208
2023-01-16 07:21 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.919 s -0.516
2023-01-16 07:22 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.184 s 0.139
2023-01-16 07:23 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.866 s -0.304
2023-01-16 07:22 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.240 s -0.019
2023-01-16 07:23 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.429 s -0.061
2023-01-16 07:22 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.332 s -0.005
2023-01-16 07:23 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.612 s -0.952
2023-01-16 07:23 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.463 s -2.845
2023-01-16 07:24 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.216 s 0.175
2023-01-16 07:24 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.268 s 0.239
2023-01-16 07:24 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.201
2023-01-16 07:24 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.532 s -0.584
2023-01-16 07:24 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.335 s 0.220
2023-01-16 07:24 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.445 s -0.165
2023-01-16 07:26 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.286
2023-01-16 07:25 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 5.986 s -0.394
2023-01-16 07:25 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.943 s -0.056
2023-01-16 07:26 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.209 s 0.301
2023-01-16 07:25 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.573 s -0.640
2023-01-16 07:26 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.253 s 0.321
2023-01-16 07:26 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.588 s 0.133
2023-01-16 07:26 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.285 s 0.269
2023-01-16 07:26 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.253
2023-01-16 07:27 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.195 s 0.316
2023-01-16 07:27 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.625 s -0.259
2023-01-16 07:27 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.614 s -0.404
2023-01-16 07:27 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.238 s 0.298
2023-01-16 07:29 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.216 s 0.290
2023-01-16 07:27 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.222 s 0.239
2023-01-16 07:28 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.325 s 0.214
2023-01-16 07:28 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.285 s 0.283
2023-01-16 07:28 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.530 s 0.151
2023-01-16 07:28 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.099 s -0.021
2023-01-16 07:29 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.268 s 0.256
2023-01-16 07:28 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.893 s -0.270
2023-01-16 07:29 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.220 s 0.248
2023-01-16 07:29 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.322 s 0.274
2023-01-16 07:30 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.665 s 0.203
2023-01-16 07:29 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.939 s 0.541
2023-01-16 07:29 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.259 s 0.249
2023-01-16 07:31 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.209 s 0.260
2023-01-16 07:31 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.268 s 0.156
2023-01-16 07:30 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.195 s 0.239
2023-01-16 07:30 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.241 s 0.303
2023-01-16 07:31 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.544 s -0.063
2023-01-16 07:30 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.880 s -0.108
2023-01-16 07:31 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.410 s -0.226
2023-01-16 07:32 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.486 s -1.277
2023-01-16 07:33 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.442 s -0.004
2023-01-16 07:32 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.327 s 0.240
2023-01-16 07:32 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.412 s -1.450
2023-01-16 07:32 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s 0.117
2023-01-16 07:33 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.444 s 0.118
2023-01-16 07:33 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.893 s -0.844
2023-01-16 07:33 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.333 s -0.211
2023-01-16 07:34 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.257 s 0.146
2023-01-16 07:34 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.680 s -2.370
2023-01-16 07:35 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.371 s 0.192
2023-01-16 07:35 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.967 s 0.053
2023-01-16 07:34 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.486 s -2.138
2023-01-16 07:35 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.321 s 0.125
2023-01-16 07:35 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.258 s 0.063
2023-01-16 07:35 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.288 s 0.084
2023-01-16 07:36 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.607 s -0.127
2023-01-16 07:37 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.738 s -1.094
2023-01-16 07:36 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.236 s -0.812
2023-01-16 07:37 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.807 s -0.544
2023-01-16 07:36 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.452 s -0.035
2023-01-16 07:37 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.916 s -2.101
2023-01-16 07:36 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.397 s -0.361
2023-01-16 07:37 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.188 s -1.882
2023-01-16 07:40 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.144 s -2.206
2023-01-16 07:42 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.215 s -2.383
2023-01-16 07:42 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.152
2023-01-16 07:42 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.242 s 0.245
2023-01-16 07:43 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.204 s 0.196
2023-01-16 07:43 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.260 s 0.251
2023-01-16 07:44 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.228 s 0.188
2023-01-16 07:44 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.309 s 0.111
2023-01-16 07:44 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.452 s 0.179
2023-01-16 07:45 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.308 s 0.057
2023-01-16 07:53 JavaScript vectorFromArray numbers 0.016 s 0.018
2023-01-16 07:53 JavaScript Iterate Vector int16Array 0.002 s 0.268
2023-01-16 07:53 JavaScript toArray Vector float64Array
2023-01-16 07:53 JavaScript Iterate Vector int8Array 0.002 s 0.050
2023-01-16 07:53 JavaScript Spread Vector uint32Array 0.007 s -2.991
2023-01-16 07:53 JavaScript toArray Vector uint32Array
2023-01-16 07:53 JavaScript toArray Vector int32Array
2023-01-16 07:53 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s 0.490
2023-01-16 07:53 JavaScript toArray Vector uint64Array
2023-01-16 07:53 JavaScript Parse write recordBatches, tracks 0.002 s -1.881
2023-01-16 07:53 JavaScript Iterate Vector int64Array 0.004 s 0.019
2023-01-16 07:53 JavaScript toArray Vector int64Array
2023-01-16 07:53 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.518
2023-01-16 07:53 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s -1.884
2023-01-16 07:53 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-16 07:53 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.192 s -1.892
2023-01-16 07:53 JavaScript Iterate Vector float32Array 0.002 s 0.519
2023-01-16 07:53 JavaScript Spread Vector float32Array 0.008 s -2.724
2023-01-16 07:53 JavaScript get Vector dictionary 0.002 s -1.176
2023-01-16 07:53 JavaScript Parse read recordBatches, tracks 0.000 s 0.390
2023-01-16 07:53 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.331
2023-01-16 07:53 JavaScript Iterate Vector numbers 0.002 s 0.446
2023-01-16 07:53 JavaScript Spread Vector int32Array 0.007 s -3.063
2023-01-16 07:53 JavaScript toArray Vector numbers
2023-01-16 07:53 JavaScript toArray Vector dictionary 0.010 s -2.289
2023-01-16 07:53 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.040
2023-01-16 07:53 JavaScript vectorFromArray booleans 0.018 s 0.134
2023-01-16 07:53 JavaScript Iterate Vector uint8Array 0.002 s -0.172
2023-01-16 07:53 JavaScript Iterate Vector uint32Array 0.002 s 0.906
2023-01-16 07:53 JavaScript Iterate Vector int32Array 0.002 s 0.288
2023-01-16 07:53 JavaScript Iterate Vector dictionary 0.004 s -0.134
2023-01-16 07:53 JavaScript vectorFromArray dictionary 0.018 s -2.820
2023-01-16 07:53 JavaScript Spread Vector uint16Array 0.007 s -2.902
2023-01-16 07:53 JavaScript Spread Vector uint64Array 0.012 s -0.204
2023-01-16 07:53 JavaScript Spread Vector int16Array 0.007 s -3.319
2023-01-16 07:53 JavaScript Spread Vector int64Array 0.012 s -0.223
2023-01-16 07:53 JavaScript get Vector uint64Array 0.003 s 0.133
2023-01-16 07:53 JavaScript Iterate Vector uint16Array 0.002 s 0.429
2023-01-16 07:53 JavaScript Iterate Vector uint64Array 0.004 s 0.028
2023-01-16 07:53 JavaScript Iterate Vector string 0.126 s 0.336
2023-01-16 07:53 JavaScript Spread Vector booleans 0.010 s -1.378
2023-01-16 07:53 JavaScript toArray Vector uint16Array
2023-01-16 07:53 JavaScript toArray Vector int16Array
2023-01-16 07:53 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.110 s -2.827
2023-01-16 07:53 JavaScript Iterate Vector float64Array 0.002 s 0.546
2023-01-16 07:53 JavaScript Iterate Vector booleans 0.004 s 0.551
2023-01-16 07:53 JavaScript Spread Vector float64Array 0.008 s -2.092
2023-01-16 07:53 JavaScript Spread Vector string 0.144 s 0.951
2023-01-16 07:53 JavaScript get Vector uint16Array 0.003 s 0.143
2023-01-16 07:53 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.314
2023-01-16 07:53 JavaScript Spread Vector uint8Array 0.007 s -2.844
2023-01-16 07:53 JavaScript Spread Vector int8Array 0.007 s -2.712
2023-01-16 07:53 JavaScript Spread Vector dictionary 0.010 s -1.558
2023-01-16 07:53 JavaScript toArray Vector uint8Array
2023-01-16 07:53 JavaScript get Vector uint8Array 0.003 s 0.121
2023-01-16 07:53 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-16 07:53 JavaScript Spread Vector numbers 0.008 s -2.289
2023-01-16 07:53 JavaScript toArray Vector int8Array
2023-01-16 07:53 JavaScript toArray Vector float32Array
2023-01-16 07:53 JavaScript get Vector int8Array 0.003 s 0.125
2023-01-16 07:53 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.319
2023-01-16 07:53 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.017
2023-01-16 07:53 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.110 s -2.800
2023-01-16 07:53 JavaScript toArray Vector booleans 0.010 s -0.557
2023-01-16 07:53 JavaScript toArray Vector string 0.143 s 1.193
2023-01-16 07:53 JavaScript get Vector int64Array 0.003 s 0.090
2023-01-16 07:53 JavaScript get Vector float64Array 0.002 s -0.125
2023-01-16 07:53 JavaScript get Vector booleans 0.002 s -0.148
2023-01-16 07:53 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.280
2023-01-16 07:53 JavaScript Table tracks, 1,000,000 0.270 s 0.047
2023-01-16 07:53 JavaScript get Vector uint32Array 0.003 s 0.137
2023-01-16 07:53 JavaScript Table 1,000,000, tracks 0.271 s 0.220
2023-01-16 07:53 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.335
2023-01-16 07:53 JavaScript get Vector int16Array 0.003 s 0.166
2023-01-16 07:53 JavaScript get Vector string 0.124 s 0.377
2023-01-16 07:53 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -1.268
2023-01-16 07:53 JavaScript Table tracks, 1,000,000 0.095 s 0.305
2023-01-16 07:53 JavaScript get Vector int32Array 0.003 s 0.187
2023-01-16 07:53 JavaScript get Vector float32Array 0.002 s 0.451
2023-01-16 07:53 JavaScript get Vector numbers 0.002 s 0.086
2023-01-16 07:53 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.395
2023-01-16 07:53 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s 1.116
2023-01-16 07:53 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.544
2023-01-16 07:53 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-16 07:53 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-16 07:53 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.186 s 0.597
2023-01-16 07:53 JavaScript Table tracks, 1,000,000 0.050 s -1.835
2023-01-16 07:53 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.151