Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-19 05:11 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.131 s 0.146
2023-01-19 05:14 Python dataframe-to-table type_strings 0.429 s -0.705
2023-01-19 05:10 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 13.266 s 1.314
2023-01-19 05:09 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.790 s -0.383
2023-01-19 05:11 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.453 s -2.145
2023-01-19 05:09 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.236 s 0.305
2023-01-19 05:14 Python dataframe-to-table type_floats 0.010 s 0.219
2023-01-19 05:10 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 13.280 s 1.381
2023-01-19 05:14 Python dataframe-to-table chi_traffic_2020_Q1 21.164 s -0.687
2023-01-19 05:14 Python dataframe-to-table type_dict 0.012 s -3.271
2023-01-19 05:22 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 84.236 s -0.105
2023-01-19 05:47 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.382
2023-01-19 05:14 Python dataset-filter nyctaxi_2010-01 1.024 s -0.129
2023-01-19 05:34 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.654 s 0.291
2023-01-19 05:11 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 11.338 s -0.802
2023-01-19 05:35 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.901
2023-01-19 05:12 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 11.337 s -0.927
2023-01-19 05:14 Python dataframe-to-table type_nested 2.976 s -0.516
2023-01-19 05:18 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 70.940 s 1.111
2023-01-19 05:39 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.425 s -1.753
2023-01-19 05:34 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.228 s 0.134
2023-01-19 05:34 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.037 s 0.279
2023-01-19 05:34 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.191 s -1.936
2023-01-19 05:34 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.307 s -1.266
2023-01-19 05:34 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.106
2023-01-19 05:14 Python dataframe-to-table type_integers 0.010 s 0.721
2023-01-19 05:33 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.176 s 0.249
2023-01-19 05:34 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.212 s -0.449
2023-01-19 05:34 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.545
2023-01-19 05:34 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.738 s 2.309
2023-01-19 05:47 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 74.107 s 2.240
2023-01-19 05:33 Python dataset-read async=True, nyctaxi_multi_ipc_s3 215.336 s 1.067
2023-01-19 05:33 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.449 s -0.744
2023-01-19 05:34 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.312 s 0.159
2023-01-19 05:34 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.029 s 0.298
2023-01-19 05:34 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.175 s -0.522
2023-01-19 05:36 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.334 s 2.307
2023-01-19 05:47 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.289 s -1.361
2023-01-19 05:35 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.939 s -1.378
2023-01-19 05:48 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.511
2023-01-19 05:52 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.413 s -2.038
2023-01-19 05:35 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s 1.363
2023-01-19 05:47 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.150
2023-01-19 05:48 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.225 s 1.133
2023-01-19 06:01 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 84.167 s 2.140
2023-01-19 05:47 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.846 s 1.962
2023-01-19 05:52 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 31.142 s -1.622
2023-01-19 06:02 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.963 s 0.305
2023-01-19 05:47 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.069 s -1.532
2023-01-19 05:52 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.406 s 1.175
2023-01-19 06:07 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.302 s -0.069
2023-01-19 06:09 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.383 s -0.499
2023-01-19 05:39 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.147 s 0.960
2023-01-19 05:39 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.147 s 1.954
2023-01-19 06:01 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.490 s 0.218
2023-01-19 06:02 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.218 s -0.004
2023-01-19 06:03 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.942 s -0.077
2023-01-19 06:02 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.327 s 0.267
2023-01-19 06:02 Python file-read lz4, feather, table, fanniemae_2016Q4 0.824 s 0.029
2023-01-19 06:03 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.589 s 0.299
2023-01-19 06:01 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.496 s 0.062
2023-01-19 06:03 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.325 s 0.410
2023-01-19 06:05 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.997 s -1.310
2023-01-19 06:08 Python file-write lz4, feather, table, fanniemae_2016Q4 1.839 s 0.129
2023-01-19 06:19 R dataframe-to-table type_strings, R 0.535 s 0.053
2023-01-19 06:22 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.568 s -0.267
2023-01-19 06:22 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.907 s 0.039
2023-01-19 06:23 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.811 s 0.291
2023-01-19 05:49 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.474 s 2.223
2023-01-19 06:03 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.923 s 0.173
2023-01-19 06:03 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.937 s 0.282
2023-01-19 06:09 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.778 s -0.448
2023-01-19 06:02 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.636 s 0.247
2023-01-19 06:02 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.978 s 0.028
2023-01-19 06:10 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.699 s 0.060
2023-01-19 06:10 Python file-write lz4, feather, table, nyctaxi_2010-01 1.762 s 0.135
2023-01-19 06:11 Python wide-dataframe use_legacy_dataset=false 0.521 s -0.381
2023-01-19 06:01 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.631 s 0.244
2023-01-19 06:01 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.614 s 0.249
2023-01-19 06:10 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.323 s -0.859
2023-01-19 06:10 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.109 s 0.014
2023-01-19 06:11 Python wide-dataframe use_legacy_dataset=true 0.378 s 0.148
2023-01-19 06:03 Python file-read lz4, feather, table, nyctaxi_2010-01 0.673 s 0.306
2023-01-19 06:08 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.879 s 0.112
2023-01-19 06:20 R dataframe-to-table type_integers, R 0.010 s 0.492
2023-01-19 06:23 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.893 s 0.278
2023-01-19 06:24 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.962 s -1.317
2023-01-19 06:35 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.808 s -0.516
2023-01-19 06:37 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.775 s -0.628
2023-01-19 06:04 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.736 s -1.096
2023-01-19 06:06 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.518 s -1.284
2023-01-19 06:08 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.893 s -0.396
2023-01-19 06:22 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.844 s 0.292
2023-01-19 06:23 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.580 s 0.252
2023-01-19 06:29 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.960 s -0.039
2023-01-19 06:05 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.358 s -1.311
2023-01-19 06:07 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.227 s -0.086
2023-01-19 06:20 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.314 s -0.099
2023-01-19 06:21 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.314 s 0.249
2023-01-19 06:33 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.444 s 1.008
2023-01-19 06:11 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.204 s -0.084
2023-01-19 06:21 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.330 s -0.830
2023-01-19 06:21 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.568 s 0.250
2023-01-19 06:22 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.216 s 0.270
2023-01-19 06:22 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.908 s -0.011
2023-01-19 06:41 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.201 s 0.215
2023-01-19 06:42 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.274 s 0.217
2023-01-19 06:43 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.290 s 0.161
2023-01-19 06:44 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.163
2023-01-19 06:48 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.638 s 0.159
2023-01-19 06:50 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.269
2023-01-19 06:50 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.507 s 0.166
2023-01-19 06:20 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.571 s -0.242
2023-01-19 06:21 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.585 s -0.794
2023-01-19 06:21 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.596 s 0.270
2023-01-19 06:22 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.562 s -0.066
2023-01-19 06:26 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.911 s -1.287
2023-01-19 06:31 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.037 s 0.050
2023-01-19 06:19 R dataframe-to-table chi_traffic_2020_Q1, R 4.379 s -0.909
2023-01-19 06:19 R dataframe-to-table type_dict, R 0.063 s -0.889
2023-01-19 06:27 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.381 s -1.346
2023-01-19 06:29 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.383 s -1.356
2023-01-19 06:34 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.997 s -0.634
2023-01-19 06:20 R dataframe-to-table type_floats, R 0.013 s 0.383
2023-01-19 06:31 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.488 s 1.467
2023-01-19 06:36 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.727 s -0.607
2023-01-19 06:44 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.269 s 0.225
2023-01-19 06:46 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.283 s -3.459
2023-01-19 06:51 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.340 s 0.297
2023-01-19 06:53 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.716 s 0.227
2023-01-19 06:20 R dataframe-to-table type_nested, R 0.574 s -0.148
2023-01-19 06:45 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.302 s 0.106
2023-01-19 06:46 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.563 s -0.141
2023-01-19 06:47 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.330 s 0.289
2023-01-19 06:48 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.265 s 0.203
2023-01-19 06:49 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.110
2023-01-19 06:39 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.480 s -4.466
2023-01-19 06:41 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.240 s 0.230
2023-01-19 06:43 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.717 s 0.514
2023-01-19 06:43 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.145
2023-01-19 06:43 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.435 s 0.097
2023-01-19 06:48 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.319 s 0.332
2023-01-19 06:41 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.201 s 0.152
2023-01-19 06:46 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.243 s -1.662
2023-01-19 06:48 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.350 s 0.219
2023-01-19 06:51 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.373 s 0.309
2023-01-19 06:38 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.315 s -1.855
2023-01-19 06:39 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.179 s -0.554
2023-01-19 06:40 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.573 s -0.575
2023-01-19 06:41 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.607 s -0.439
2023-01-19 06:42 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.281 s 0.217
2023-01-19 06:46 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.342 s -3.354
2023-01-19 06:47 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.201 s -0.116
2023-01-19 06:48 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.313 s 0.222
2023-01-19 06:41 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.600 s -0.951
2023-01-19 06:42 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.004 s 0.028
2023-01-19 06:44 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.064 s -0.296
2023-01-19 06:44 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.232 s 0.221
2023-01-19 06:45 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.588 s 0.148
2023-01-19 06:46 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.242 s 0.309
2023-01-19 06:51 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.272
2023-01-19 06:40 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.078 s -0.389
2023-01-19 06:44 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.666 s -0.614
2023-01-19 06:44 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.303 s 0.247
2023-01-19 06:47 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.919 s -0.146
2023-01-19 06:52 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.660 s 0.225
2023-01-19 06:41 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.253 s -0.089
2023-01-19 06:42 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.589 s 0.002
2023-01-19 06:43 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -0.072
2023-01-19 06:43 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.339 s -0.094
2023-01-19 06:45 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.897 s 0.073
2023-01-19 06:47 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.272 s 0.173
2023-01-19 06:48 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.161
2023-01-19 06:49 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.734 s -0.415
2023-01-19 06:49 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.202 s 0.204
2023-01-19 06:43 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.349 s 0.163
2023-01-19 06:50 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.357 s -0.090
2023-01-19 06:51 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.293 s 0.289
2023-01-19 06:55 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.766 s 0.319
2023-01-19 06:49 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.635 s -0.023
2023-01-19 06:50 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.161 s 0.167
2023-01-19 06:50 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.179 s 0.160
2023-01-19 06:51 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.255 s 0.093
2023-01-19 06:51 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.351 s 0.244
2023-01-19 06:52 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.651 s -0.195
2023-01-19 06:53 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.397 s 0.218
2023-01-19 06:52 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.784 s 0.142
2023-01-19 06:53 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.334 s 0.250
2023-01-19 06:53 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.428 s 0.252
2023-01-19 06:53 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.339 s 0.250
2023-01-19 06:53 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.370 s 0.223
2023-01-19 06:54 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.784 s -0.082
2023-01-19 06:55 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.295 s 0.332
2023-01-19 06:54 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.613 s 0.303
2023-01-19 06:54 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.273 s 0.236
2023-01-19 06:54 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.324 s 0.316
2023-01-19 06:55 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.370 s 0.341
2023-01-19 06:55 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.442 s 0.099
2023-01-19 06:56 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.256 s 0.190
2023-01-19 06:56 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.977 s -0.898
2023-01-19 06:57 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.336 s 0.270
2023-01-19 06:56 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.175 s -0.237
2023-01-19 06:56 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.299 s 0.315
2023-01-19 06:56 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.261 s 0.195
2023-01-19 06:57 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.322 s 0.100
2023-01-19 06:58 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.747 s 0.001
2023-01-19 06:58 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.210 s 0.185
2023-01-19 06:57 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.652 s 0.187
2023-01-19 06:58 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.201
2023-01-19 06:57 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.875 s 0.099
2023-01-19 06:58 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.304 s 0.233
2023-01-19 06:59 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.877 s -0.673
2023-01-19 06:58 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.231 s 0.215
2023-01-19 06:59 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.542 s -0.085
2023-01-19 06:58 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.330 s 0.082
2023-01-19 06:59 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.274 s -0.522
2023-01-19 07:00 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.365 s 0.152
2023-01-19 07:00 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.919 s -0.327
2023-01-19 06:59 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.304 s -0.078
2023-01-19 06:59 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s 0.225
2023-01-19 06:59 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.256 s 0.189
2023-01-19 07:00 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.498 s -1.124
2023-01-19 07:01 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.682 s -1.217
2023-01-19 07:01 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.183 s 0.188
2023-01-19 07:01 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.556 s -0.477
2023-01-19 07:01 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.240 s 0.068
2023-01-19 07:01 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.333 s 0.009
2023-01-19 07:02 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.429 s 0.002
2023-01-19 07:02 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.615 s -0.899
2023-01-19 07:02 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.864 s -0.145
2023-01-19 07:02 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.443 s -1.260
2023-01-19 07:03 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.266 s 0.295
2023-01-19 07:03 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.334 s 0.234
2023-01-19 07:03 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.536 s -0.328
2023-01-19 07:03 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.217
2023-01-19 07:03 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.221 s 0.045
2023-01-19 07:03 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.443 s 0.058
2023-01-19 07:04 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.937 s 0.068
2023-01-19 07:05 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.209 s 0.293
2023-01-19 07:04 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.458 s 1.788
2023-01-19 07:05 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.586 s 0.225
2023-01-19 07:05 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.262
2023-01-19 07:05 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 6.055 s -0.476
2023-01-19 07:05 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.345
2023-01-19 07:05 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.285 s 0.305
2023-01-19 07:05 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.304
2023-01-19 07:06 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.604 s 0.711
2023-01-19 07:06 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.196 s 0.254
2023-01-19 07:07 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.326 s 0.150
2023-01-19 07:07 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.222 s 0.225
2023-01-19 07:06 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.651 s -0.731
2023-01-19 07:06 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.237 s 0.285
2023-01-19 07:07 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.530 s 0.144
2023-01-19 07:08 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.112 s -0.054
2023-01-19 07:07 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.285 s 0.248
2023-01-19 07:08 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.269 s 0.236
2023-01-19 07:07 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.892 s -0.279
2023-01-19 07:08 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.221 s 0.214
2023-01-19 07:08 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.217 s 0.261
2023-01-19 07:08 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.989 s -0.157
2023-01-19 07:08 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.320 s 0.337
2023-01-19 07:08 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.259 s 0.229
2023-01-19 07:09 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.982 s -0.279
2023-01-19 07:09 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.667 s 0.071
2023-01-19 07:09 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.195 s 0.183
2023-01-19 07:10 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.241 s 0.273
2023-01-19 07:10 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.543 s 0.003
2023-01-19 07:10 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.265 s 0.225
2023-01-19 07:10 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.210 s 0.153
2023-01-19 07:10 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.412 s -0.333
2023-01-19 07:11 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.492 s -1.332
2023-01-19 07:12 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.327 s 0.195
2023-01-19 07:11 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s 0.095
2023-01-19 07:11 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.339 s -0.534
2023-01-19 07:12 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.438 s 0.239
2023-01-19 07:12 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.887 s 0.172
2023-01-19 07:12 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.442 s 0.210
2023-01-19 07:14 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.436 s -0.853
2023-01-19 07:13 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.655 s -0.833
2023-01-19 07:14 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.257 s 0.154
2023-01-19 07:22 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.308 s 0.220
2023-01-19 07:14 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.258 s 0.131
2023-01-19 07:12 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.332 s -0.032
2023-01-19 07:14 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.321 s 0.164
2023-01-19 07:14 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.288 s 0.046
2023-01-19 07:16 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.452 s 0.015
2023-01-19 07:22 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.227 s 0.161
2023-01-19 07:16 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.893 s -0.575
2023-01-19 07:21 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 32.766 s -0.223
2023-01-19 07:22 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.457 s -0.084
2023-01-19 07:22 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.331 s -0.183
2023-01-19 07:14 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.370 s 0.222
2023-01-19 07:15 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.603 s 0.220
2023-01-19 07:21 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.242 s 0.242
2023-01-19 07:14 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.965 s 0.142
2023-01-19 07:15 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.396 s -0.046
2023-01-19 07:16 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.737 s -0.855
2023-01-19 07:21 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.261 s 0.207
2023-01-19 07:15 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.068 s 0.031
2023-01-19 07:16 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.805 s -0.450
2023-01-19 07:17 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.203 s -1.728
2023-01-19 07:19 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.176 s -1.777
2023-01-19 07:21 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.199 s 0.103
2023-01-19 07:21 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.204 s 0.218
2023-01-19 07:31 JavaScript toArray Vector int8Array
2023-01-19 07:31 JavaScript toArray Vector int32Array
2023-01-19 07:31 JavaScript toArray Vector float32Array
2023-01-19 07:31 JavaScript get Vector dictionary 0.002 s -2.247
2023-01-19 07:31 JavaScript Iterate Vector uint8Array 0.002 s 1.562
2023-01-19 07:31 JavaScript Iterate Vector uint32Array 0.002 s 0.710
2023-01-19 07:31 JavaScript Iterate Vector int8Array 0.002 s 0.443
2023-01-19 07:31 JavaScript vectorFromArray numbers 0.016 s 0.213
2023-01-19 07:31 JavaScript vectorFromArray dictionary 0.017 s -1.818
2023-01-19 07:31 JavaScript Iterate Vector uint64Array 0.004 s 0.253
2023-01-19 07:31 JavaScript Spread Vector float64Array 0.008 s 1.105
2023-01-19 07:31 JavaScript Spread Vector booleans 0.010 s 0.431
2023-01-19 07:31 JavaScript Spread Vector string 0.144 s 1.091
2023-01-19 07:31 JavaScript get Vector uint32Array 0.003 s -0.048
2023-01-19 07:31 JavaScript get Vector int8Array 0.003 s 0.268
2023-01-19 07:31 JavaScript get Vector int32Array 0.003 s -0.227
2023-01-19 07:31 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.192 s -1.624
2023-01-19 07:31 JavaScript vectorFromArray booleans 0.018 s -0.261
2023-01-19 07:31 JavaScript Spread Vector numbers 0.008 s 0.711
2023-01-19 07:31 JavaScript toArray Vector uint8Array
2023-01-19 07:31 JavaScript toArray Vector uint32Array
2023-01-19 07:31 JavaScript toArray Vector uint16Array
2023-01-19 07:31 JavaScript toArray Vector uint64Array
2023-01-19 07:31 JavaScript toArray Vector booleans 0.010 s 0.417
2023-01-19 07:31 JavaScript get Vector uint16Array 0.003 s -0.050
2023-01-19 07:31 JavaScript Iterate Vector uint16Array 0.002 s 0.673
2023-01-19 07:31 JavaScript Iterate Vector float64Array 0.002 s 0.777
2023-01-19 07:31 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.770
2023-01-19 07:31 JavaScript Iterate Vector int16Array 0.002 s 0.694
2023-01-19 07:31 JavaScript Iterate Vector int64Array 0.004 s 0.174
2023-01-19 07:31 JavaScript Iterate Vector booleans 0.004 s 0.891
2023-01-19 07:31 JavaScript Iterate Vector string 0.126 s 0.263
2023-01-19 07:31 JavaScript Spread Vector uint16Array 0.006 s 0.360
2023-01-19 07:31 JavaScript toArray Vector int64Array
2023-01-19 07:31 JavaScript Iterate Vector int32Array 0.002 s 0.461
2023-01-19 07:31 JavaScript Iterate Vector float32Array 0.002 s 0.080
2023-01-19 07:31 JavaScript Iterate Vector numbers 0.002 s 0.671
2023-01-19 07:31 JavaScript Iterate Vector dictionary 0.004 s -0.150
2023-01-19 07:31 JavaScript Spread Vector uint8Array 0.006 s 0.519
2023-01-19 07:31 JavaScript Spread Vector uint32Array 0.007 s 0.548
2023-01-19 07:31 JavaScript Spread Vector int8Array 0.006 s 0.131
2023-01-19 07:31 JavaScript Spread Vector int32Array 0.006 s 0.671
2023-01-19 07:31 JavaScript get Vector float32Array 0.002 s -1.458
2023-01-19 07:31 JavaScript get Vector numbers 0.002 s -0.108
2023-01-19 07:31 JavaScript Spread Vector uint64Array 0.012 s -0.583
2023-01-19 07:31 JavaScript Spread Vector int16Array 0.006 s 0.364
2023-01-19 07:31 JavaScript Spread Vector int64Array 0.012 s -0.836
2023-01-19 07:31 JavaScript toArray Vector int16Array
2023-01-19 07:31 JavaScript toArray Vector float64Array
2023-01-19 07:31 JavaScript toArray Vector string 0.143 s 1.302
2023-01-19 07:31 JavaScript Parse read recordBatches, tracks 0.000 s -6.510
2023-01-19 07:31 JavaScript Spread Vector float32Array 0.008 s 1.538
2023-01-19 07:31 JavaScript Spread Vector dictionary 0.010 s -0.071
2023-01-19 07:31 JavaScript toArray Vector dictionary 0.010 s -0.171
2023-01-19 07:31 JavaScript get Vector uint8Array 0.003 s -0.369
2023-01-19 07:31 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.550
2023-01-19 07:31 JavaScript toArray Vector numbers
2023-01-19 07:31 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.236
2023-01-19 07:31 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-19 07:31 JavaScript get Vector uint64Array 0.003 s -0.104
2023-01-19 07:31 JavaScript get Vector string 0.124 s 0.238
2023-01-19 07:31 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.574
2023-01-19 07:31 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.187 s 0.415
2023-01-19 07:31 JavaScript get Vector int16Array 0.003 s 0.017
2023-01-19 07:31 JavaScript get Vector int64Array 0.003 s -0.248
2023-01-19 07:31 JavaScript Parse write recordBatches, tracks 0.002 s -3.804
2023-01-19 07:31 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.270
2023-01-19 07:31 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.531
2023-01-19 07:31 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-19 07:31 JavaScript get Vector float64Array 0.002 s -0.254
2023-01-19 07:31 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-19 07:31 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-19 07:31 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.636
2023-01-19 07:31 JavaScript Table tracks, 1,000,000 0.258 s 0.666
2023-01-19 07:31 JavaScript Table tracks, 1,000,000 0.095 s -0.456
2023-01-19 07:31 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.432
2023-01-19 07:31 JavaScript get Vector booleans 0.002 s 0.643
2023-01-19 07:31 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.200
2023-01-19 07:31 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.293
2023-01-19 07:31 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.293
2023-01-19 07:31 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.166
2023-01-19 07:31 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.535
2023-01-19 07:31 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.016
2023-01-19 07:31 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.797
2023-01-19 07:31 JavaScript Table tracks, 1,000,000 0.050 s 0.066
2023-01-19 07:31 JavaScript Table 1,000,000, tracks 0.249 s 1.184
2023-01-19 07:31 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.638
2023-01-19 07:31 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s 0.646