Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-14 13:49 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.781 s 0.150
2023-01-14 13:49 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.263 s 0.072
2023-01-14 13:50 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.085 s -1.224
2023-01-14 13:50 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.122 s -1.478
2023-01-14 13:51 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.439 s -0.161
2023-01-14 13:51 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.105 s 0.364
2023-01-14 13:51 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.539 s 1.135
2023-01-14 13:52 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.404 s 1.295
2023-01-14 13:54 Python dataframe-to-table chi_traffic_2020_Q1 20.963 s 1.035
2023-01-14 13:54 Python dataframe-to-table type_strings 0.430 s -0.884
2023-01-14 13:54 Python dataframe-to-table type_integers 0.010 s 0.897
2023-01-14 13:54 Python dataframe-to-table type_dict 0.011 s 0.619
2023-01-14 13:54 Python dataframe-to-table type_nested 2.939 s 1.533
2023-01-14 13:54 Python dataframe-to-table type_floats 0.010 s 0.189
2023-01-14 13:55 Python dataset-filter nyctaxi_2010-01 1.274 s -6.135
2023-01-14 13:58 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 75.598 s 0.597
2023-01-14 14:15 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.176 s -0.887
2023-01-14 14:15 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.138 s -0.282
2023-01-14 14:14 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.183 s 0.111
2023-01-14 14:15 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.042 s 0.226
2023-01-14 14:14 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.252 s 0.468
2023-01-14 14:15 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.675 s 0.180
2023-01-14 14:03 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 84.201 s -0.614
2023-01-14 14:15 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.213 s -0.555
2023-01-14 14:14 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.309 s 0.128
2023-01-14 14:15 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.360
2023-01-14 14:14 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.252 s -0.155
2023-01-14 14:15 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.306 s -2.450
2023-01-14 14:15 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.932 s -2.358
2023-01-14 14:28 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.046 s 0.421
2023-01-14 14:28 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.227
2023-01-14 14:33 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.414 s -2.350
2023-01-14 14:14 Python dataset-read async=True, nyctaxi_multi_ipc_s3 221.836 s 0.104
2023-01-14 14:14 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.039 s 0.248
2023-01-14 14:20 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.149 s 0.067
2023-01-14 14:15 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.361
2023-01-14 14:15 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.425
2023-01-14 14:28 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.866 s 0.545
2023-01-14 14:15 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.758 s 0.243
2023-01-14 14:20 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.151 s 0.057
2023-01-14 14:16 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.388
2023-01-14 14:16 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.535 s 0.277
2023-01-14 14:19 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.308 s -2.658
2023-01-14 14:28 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.225 s 0.891
2023-01-14 14:29 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.695 s 0.509
2023-01-14 14:42 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.514 s -0.692
2023-01-14 14:33 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.412 s -0.727
2023-01-14 14:43 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.952 s -0.219
2023-01-14 14:44 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.584 s 0.333
2023-01-14 14:44 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.343 s 0.171
2023-01-14 14:48 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.334 s -0.128
2023-01-14 14:28 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.709
2023-01-14 14:28 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.046 s -2.540
2023-01-14 14:28 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.287 s -2.360
2023-01-14 14:28 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.227 s -2.179
2023-01-14 14:43 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.987 s -0.131
2023-01-14 14:47 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.424 s -1.510
2023-01-14 14:49 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.909 s 0.246
2023-01-14 14:50 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.396 s -1.145
2023-01-14 14:51 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.282 s -1.178
2023-01-14 14:43 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.627 s 0.376
2023-01-14 14:45 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.720 s -1.985
2023-01-14 14:44 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.933 s 0.338
2023-01-14 14:48 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.368 s -0.116
2023-01-14 14:50 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.810 s -1.373
2023-01-14 15:01 R dataframe-to-table type_integers, R 0.010 s -0.052
2023-01-14 15:02 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.334 s -0.647
2023-01-14 15:03 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.911 s -0.145
2023-01-14 15:13 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.491 s 0.162
2023-01-14 14:33 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.891 s -2.614
2023-01-14 14:42 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.507 s -0.217
2023-01-14 14:49 Python file-write lz4, feather, table, fanniemae_2016Q4 1.852 s 0.019
2023-01-14 14:51 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.818 s -0.395
2023-01-14 14:42 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.642 s 0.144
2023-01-14 14:44 Python file-read lz4, feather, table, nyctaxi_2010-01 0.668 s 0.378
2023-01-14 14:46 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.258 s -1.397
2023-01-14 14:52 Python wide-dataframe use_legacy_dataset=false 0.504 s 1.399
2023-01-14 15:00 R dataframe-to-table type_dict, R 0.047 s 1.399
2023-01-14 15:21 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.091 s -1.121
2023-01-14 15:21 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.585 s -0.577
2023-01-14 14:42 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.632 s -0.004
2023-01-14 14:43 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.317 s 0.347
2023-01-14 14:51 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.203 s 0.032
2023-01-14 14:52 Python wide-dataframe use_legacy_dataset=true 0.374 s 0.480
2023-01-14 14:42 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.286 s 0.576
2023-01-14 14:43 Python file-read lz4, feather, table, fanniemae_2016Q4 0.822 s 0.162
2023-01-14 14:43 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.985 s -0.058
2023-01-14 14:46 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.900 s -2.156
2023-01-14 15:00 R dataframe-to-table chi_traffic_2020_Q1, R 4.389 s -1.786
2023-01-14 15:01 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.319 s -0.035
2023-01-14 14:43 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.212 s 0.573
2023-01-14 14:44 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.925 s 0.136
2023-01-14 14:49 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.899 s -0.906
2023-01-14 15:01 R dataframe-to-table type_nested, R 0.573 s -0.185
2023-01-14 15:03 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.218 s 0.326
2023-01-14 15:12 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.493 s -0.226
2023-01-14 15:22 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.200 s 0.216
2023-01-14 15:24 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.335 s 0.177
2023-01-14 15:25 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.231 s 0.227
2023-01-14 15:26 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.496 s -0.046
2023-01-14 15:28 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.191 s -0.023
2023-01-14 14:51 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.129 s 0.032
2023-01-14 15:02 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.594 s 0.303
2023-01-14 15:04 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.892 s 0.312
2023-01-14 15:16 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.804 s -1.531
2023-01-14 15:18 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.310 s 0.211
2023-01-14 15:23 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.785 s -0.120
2023-01-14 15:24 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.348 s 0.183
2023-01-14 15:25 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.036 s 0.383
2023-01-14 15:26 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.904 s -0.230
2023-01-14 15:27 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.201 s 0.189
2023-01-14 15:27 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.272 s 0.042
2023-01-14 15:28 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.189
2023-01-14 15:30 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.161 s 0.172
2023-01-14 15:31 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.289 s 0.308
2023-01-14 15:35 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.295 s 0.252
2023-01-14 15:24 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.096
2023-01-14 15:25 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.579 s 0.288
2023-01-14 15:28 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.922 s -0.303
2023-01-14 15:30 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.504 s 0.226
2023-01-14 15:33 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.377 s -1.972
2023-01-14 15:34 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.613 s 0.225
2023-01-14 15:36 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.953 s 0.252
2023-01-14 15:38 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.209 s 0.199
2023-01-14 15:40 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.291 s -9.122
2023-01-14 15:45 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 5.733 s 0.304
2023-01-14 15:47 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.521 s 0.325
2023-01-14 15:48 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.321 s 0.235
2023-01-14 15:49 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.257 s 0.219
2023-01-14 14:51 Python file-write lz4, feather, table, nyctaxi_2010-01 1.791 s 0.021
2023-01-14 15:01 R dataframe-to-table type_floats, R 0.013 s 0.655
2023-01-14 15:01 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.574 s -0.227
2023-01-14 15:00 R dataframe-to-table type_strings, R 0.534 s 0.169
2023-01-14 15:03 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.570 s -0.309
2023-01-14 15:04 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.580 s 0.291
2023-01-14 15:07 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.822 s -1.986
2023-01-14 15:09 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.270 s -1.903
2023-01-14 15:14 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.986 s -1.632
2023-01-14 15:19 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.189 s -0.983
2023-01-14 15:22 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.605 s -0.629
2023-01-14 15:23 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.581 s 0.175
2023-01-14 15:25 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.269 s 0.182
2023-01-14 15:25 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.302 s 0.239
2023-01-14 15:26 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.262
2023-01-14 15:31 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.356 s -0.064
2023-01-14 15:33 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.337 s 0.267
2023-01-14 15:37 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.653 s 0.035
2023-01-14 15:03 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.913 s -0.191
2023-01-14 15:03 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.810 s 0.336
2023-01-14 15:12 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.040 s -0.024
2023-01-14 15:17 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.714 s -1.537
2023-01-14 15:30 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.339
2023-01-14 15:31 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.291 s 0.310
2023-01-14 15:32 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.349 s 0.262
2023-01-14 15:32 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.786 s -0.066
2023-01-14 15:34 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.367 s 0.268
2023-01-14 15:35 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.271 s 0.284
2023-01-14 15:35 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.439 s 0.264
2023-01-14 15:39 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.328 s 0.226
2023-01-14 15:40 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.301 s 0.076
2023-01-14 15:40 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.474 s 0.124
2023-01-14 15:41 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.523 s 0.823
2023-01-14 15:42 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.237 s -0.003
2023-01-14 15:42 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.425 s -0.151
2023-01-14 15:44 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.920 s 0.240
2023-01-14 15:02 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.568 s 0.258
2023-01-14 15:02 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.852 s 0.215
2023-01-14 15:05 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.867 s -2.203
2023-01-14 15:10 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.958 s 0.152
2023-01-14 15:18 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.760 s -1.523
2023-01-14 15:23 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -0.139
2023-01-14 15:24 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.647 s 0.456
2023-01-14 15:28 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.320 s 0.194
2023-01-14 15:30 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.160 s 0.267
2023-01-14 15:32 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.372 s 0.301
2023-01-14 15:33 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.448 s -1.472
2023-01-14 15:35 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.322 s 0.328
2023-01-14 15:35 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.370 s 0.251
2023-01-14 15:35 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.762 s 0.359
2023-01-14 15:38 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.216
2023-01-14 15:47 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.222 s 0.222
2023-01-14 15:48 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.219 s 0.188
2023-01-14 15:50 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.240 s 0.284
2023-01-14 15:50 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.267 s 0.085
2023-01-14 15:02 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.579 s -0.398
2023-01-14 15:02 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.317 s 0.219
2023-01-14 15:03 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.570 s -0.367
2023-01-14 15:08 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.282 s -2.178
2023-01-14 15:24 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.290 s 0.069
2023-01-14 15:25 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.227 s 0.208
2023-01-14 15:28 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.349 s 0.242
2023-01-14 15:33 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.429 s 0.149
2023-01-14 15:37 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.298 s 0.299
2023-01-14 15:38 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.688 s 0.253
2023-01-14 15:42 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.331 s -0.023
2023-01-14 15:43 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.296 s 0.213
2023-01-14 15:44 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.241 s 0.126
2023-01-14 15:47 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.328 s 0.038
2023-01-14 15:48 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.886 s -0.062
2023-01-14 15:49 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.911 s 1.021
2023-01-14 15:50 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.665 s 0.376
2023-01-14 16:01 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 32.662 s -0.651
2023-01-14 15:20 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.470 s 0.075
2023-01-14 15:21 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.559 s 0.096
2023-01-14 15:22 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.201 s 0.153
2023-01-14 15:22 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.275 s -0.071
2023-01-14 15:23 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.006 s -0.173
2023-01-14 15:25 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.301 s 0.074
2023-01-14 15:27 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.235 s 0.109
2023-01-14 15:27 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.243 s 0.197
2023-01-14 15:27 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.328 s 0.326
2023-01-14 15:29 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.634 s 0.224
2023-01-14 15:29 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.642 s 0.377
2023-01-14 15:31 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.339 s 0.300
2023-01-14 15:32 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.654 s 0.236
2023-01-14 15:34 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.710 s 0.257
2023-01-14 15:34 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.713 s 0.083
2023-01-14 15:37 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.262 s 0.001
2023-01-14 15:38 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.302 s 0.241
2023-01-14 15:39 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.532 s 0.240
2023-01-14 15:39 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.148 s 0.376
2023-01-14 15:40 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.254 s 0.212
2023-01-14 15:22 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.248 s 0.756
2023-01-14 15:22 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.239 s 0.230
2023-01-14 15:22 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.281 s 0.176
2023-01-14 15:24 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.432 s 0.154
2023-01-14 15:28 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.265 s 0.230
2023-01-14 15:29 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.635 s -0.158
2023-01-14 15:37 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.334 s 0.279
2023-01-14 15:38 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.876 s 0.282
2023-01-14 15:42 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.854 s -0.356
2023-01-14 15:44 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.337 s 0.027
2023-01-14 15:49 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.663 s 0.226
2023-01-14 15:50 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.194 s 0.203
2023-01-14 15:50 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.208 s 0.243
2023-01-14 15:53 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.323 s 0.022
2023-01-14 16:02 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.311 s -0.023
2023-01-14 15:28 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.312 s 0.274
2023-01-14 15:30 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.201 s 0.240
2023-01-14 15:30 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.178 s 0.289
2023-01-14 15:31 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.236 s 0.049
2023-01-14 15:33 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.553 s 0.217
2023-01-14 15:36 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.124 s -0.198
2023-01-14 15:37 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.320 s 0.314
2023-01-14 15:40 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.858 s 0.412
2023-01-14 15:47 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.196 s 0.260
2023-01-14 15:48 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.215 s 0.241
2023-01-14 15:52 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.441 s -0.076
2023-01-14 15:55 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.287 s 0.170
2023-01-14 15:56 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.075 s -0.375
2023-01-14 15:56 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.449 s 0.067
2023-01-14 15:57 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.139 s -1.252
2023-01-14 16:01 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.074
2023-01-14 15:36 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.255 s 0.197
2023-01-14 15:44 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.430 s -5.986
2023-01-14 15:47 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.283 s 0.281
2023-01-14 15:48 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.034 s 0.390
2023-01-14 15:52 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.309 s -0.958
2023-01-14 15:54 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.319 s 0.202
2023-01-14 15:55 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.609 s -0.383
2023-01-14 16:11 JavaScript Iterate Vector uint32Array 0.002 s 0.460
2023-01-14 15:38 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.230 s 0.188
2023-01-14 15:39 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.869 s -0.202
2023-01-14 15:43 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.555 s -1.310
2023-01-14 15:45 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.261
2023-01-14 15:46 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.581 s 0.220
2023-01-14 15:48 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.267 s 0.224
2023-01-14 15:52 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.326 s 0.197
2023-01-14 15:52 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.442 s 0.141
2023-01-14 15:54 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.369 s 0.258
2023-01-14 15:55 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.942 s 0.514
2023-01-14 15:57 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.883 s -0.843
2023-01-14 16:02 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.449 s 0.220
2023-01-14 15:40 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.363 s 0.124
2023-01-14 15:41 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.143 s 0.282
2023-01-14 15:42 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.589 s 0.245
2023-01-14 15:44 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.440 s -0.006
2023-01-14 15:45 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.471 s 1.543
2023-01-14 15:45 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.191
2023-01-14 15:46 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.143
2023-01-14 15:46 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.622 s -0.326
2023-01-14 15:56 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.792 s 0.009
2023-01-14 16:02 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.280 s 0.293
2023-01-14 15:41 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.183 s 0.172
2023-01-14 15:43 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.329 s -7.835
2023-01-14 15:45 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.210 s 0.169
2023-01-14 15:51 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.442 s 0.274
2023-01-14 15:52 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.273 s 0.048
2023-01-14 15:52 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.891 s -0.671
2023-01-14 15:53 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.650 s -2.256
2023-01-14 15:54 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.256 s 0.150
2023-01-14 16:11 JavaScript Iterate Vector uint64Array 0.004 s 0.183
2023-01-14 16:11 JavaScript Spread Vector int64Array 0.012 s 0.099
2023-01-14 15:46 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.285 s 0.153
2023-01-14 15:47 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.551 s 0.043
2023-01-14 15:47 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.237 s 0.289
2023-01-14 15:50 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.402 s 0.371
2023-01-14 15:56 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.396 s -0.335
2023-01-14 15:56 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.733 s -0.836
2023-01-14 15:59 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 29.909 s -1.351
2023-01-14 16:01 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.242 s 0.137
2023-01-14 16:11 JavaScript Spread Vector int8Array 0.006 s 0.551
2023-01-14 15:51 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.533 s 0.197
2023-01-14 15:54 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.256 s 0.171
2023-01-14 16:02 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.261 s 0.174
2023-01-14 16:02 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.228 s 0.142
2023-01-14 16:11 JavaScript Iterate Vector booleans 0.004 s 0.757
2023-01-14 16:11 JavaScript Iterate Vector string 0.124 s 1.763
2023-01-14 15:54 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.192 s 0.521
2023-01-14 16:01 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.204 s 0.158
2023-01-14 16:11 JavaScript Iterate Vector int32Array 0.002 s 0.599
2023-01-14 16:11 JavaScript Iterate Vector float32Array 0.002 s 0.603
2023-01-14 16:11 JavaScript Iterate Vector int16Array 0.002 s 0.395
2023-01-14 16:11 JavaScript Iterate Vector int64Array 0.004 s 0.155
2023-01-14 16:11 JavaScript toArray Vector float64Array
2023-01-14 16:11 JavaScript vectorFromArray booleans 0.017 s 0.603
2023-01-14 16:11 JavaScript Iterate Vector uint8Array 0.002 s 0.178
2023-01-14 16:11 JavaScript Spread Vector int32Array 0.006 s 0.329
2023-01-14 16:11 JavaScript Spread Vector float32Array 0.008 s -1.604
2023-01-14 16:11 JavaScript Table tracks, 1,000,000 0.279 s -0.410
2023-01-14 16:11 JavaScript vectorFromArray numbers 0.016 s 0.719
2023-01-14 16:11 JavaScript Iterate Vector float64Array 0.002 s 0.867
2023-01-14 16:11 JavaScript Spread Vector uint64Array 0.012 s 0.124
2023-01-14 16:11 JavaScript toArray Vector int16Array
2023-01-14 16:11 JavaScript Iterate Vector int8Array 0.002 s 0.106
2023-01-14 16:11 JavaScript get Vector numbers 0.002 s 0.079
2023-01-14 16:11 JavaScript get Vector dictionary 0.002 s 1.369
2023-01-14 16:11 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.774
2023-01-14 16:11 JavaScript vectorFromArray dictionary 0.017 s 0.361
2023-01-14 16:11 JavaScript Iterate Vector uint16Array 0.002 s 0.572
2023-01-14 16:11 JavaScript Spread Vector int16Array 0.006 s 0.731
2023-01-14 16:11 JavaScript Spread Vector booleans 0.010 s 0.553
2023-01-14 16:11 JavaScript Spread Vector string 0.144 s 1.226
2023-01-14 16:11 JavaScript Iterate Vector numbers 0.002 s 0.762
2023-01-14 16:11 JavaScript Iterate Vector dictionary 0.004 s -1.840
2023-01-14 16:11 JavaScript Spread Vector uint8Array 0.006 s 0.438
2023-01-14 16:11 JavaScript Spread Vector uint32Array 0.007 s 0.363
2023-01-14 16:11 JavaScript Spread Vector uint16Array 0.006 s 0.134
2023-01-14 16:11 JavaScript get Vector int16Array 0.003 s 0.252
2023-01-14 16:11 JavaScript get Vector int64Array 0.003 s 0.319
2023-01-14 16:11 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.666
2023-01-14 16:11 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-14 16:11 JavaScript Spread Vector float64Array 0.008 s 0.996
2023-01-14 16:11 JavaScript toArray Vector uint64Array
2023-01-14 16:11 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.316
2023-01-14 16:11 JavaScript Table tracks, 1,000,000 0.094 s 1.211
2023-01-14 16:11 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.430
2023-01-14 16:11 JavaScript Spread Vector numbers 0.008 s 0.898
2023-01-14 16:11 JavaScript toArray Vector int8Array
2023-01-14 16:11 JavaScript toArray Vector float32Array
2023-01-14 16:11 JavaScript toArray Vector dictionary 0.010 s -0.275
2023-01-14 16:11 JavaScript get Vector int8Array 0.003 s 0.246
2023-01-14 16:11 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.271
2023-01-14 16:11 JavaScript Spread Vector dictionary 0.010 s -0.701
2023-01-14 16:11 JavaScript toArray Vector uint32Array
2023-01-14 16:11 JavaScript get Vector uint32Array 0.003 s 0.313
2023-01-14 16:11 JavaScript get Vector int32Array 0.003 s 0.294
2023-01-14 16:11 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -2.766
2023-01-14 16:11 JavaScript Table 1,000,000, tracks 0.311 s -1.636
2023-01-14 16:11 JavaScript toArray Vector uint8Array
2023-01-14 16:11 JavaScript toArray Vector int32Array
2023-01-14 16:11 JavaScript toArray Vector numbers
2023-01-14 16:11 JavaScript get Vector uint8Array 0.003 s 0.241
2023-01-14 16:11 JavaScript get Vector float32Array 0.002 s -0.705
2023-01-14 16:11 JavaScript toArray Vector uint16Array
2023-01-14 16:11 JavaScript toArray Vector string 0.146 s -0.432
2023-01-14 16:11 JavaScript get Vector uint16Array 0.003 s 0.296
2023-01-14 16:11 JavaScript get Vector float64Array 0.002 s 0.836
2023-01-14 16:11 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-14 16:11 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.189 s -0.518
2023-01-14 16:11 JavaScript toArray Vector int64Array
2023-01-14 16:11 JavaScript get Vector booleans 0.002 s 0.434
2023-01-14 16:11 JavaScript toArray Vector booleans 0.010 s 1.288
2023-01-14 16:11 JavaScript get Vector uint64Array 0.003 s 0.376
2023-01-14 16:11 JavaScript get Vector string 0.124 s 0.208
2023-01-14 16:11 JavaScript Parse write recordBatches, tracks 0.002 s 2.794
2023-01-14 16:11 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.455
2023-01-14 16:11 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s -0.492
2023-01-14 16:11 JavaScript Parse read recordBatches, tracks 0.000 s 0.795
2023-01-14 16:11 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.363
2023-01-14 16:11 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s -0.664
2023-01-14 16:11 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s -2.165
2023-01-14 16:11 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-14 16:11 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-14 16:11 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.190 s -0.805
2023-01-14 16:11 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.009
2023-01-14 16:11 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s -2.339
2023-01-14 16:11 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -2.737
2023-01-14 16:11 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.571
2023-01-14 16:11 JavaScript Table tracks, 1,000,000 0.051 s -2.803
2023-01-14 16:11 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s -0.065
2023-01-14 16:11 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -0.508