Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-20 00:53 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.257 s 0.022
2023-01-20 00:52 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.786 s -0.251
2023-01-20 00:56 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.314 s 1.140
2023-01-20 00:58 Python dataframe-to-table type_strings 0.432 s -1.720
2023-01-20 00:58 Python dataframe-to-table type_integers 0.010 s -1.185
2023-01-20 00:55 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.452 s 0.984
2023-01-20 00:53 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.146 s -1.066
2023-01-20 00:55 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.123 s 0.124
2023-01-20 00:54 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.435 s 0.455
2023-01-20 00:54 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.163 s -1.185
2023-01-20 00:58 Python dataframe-to-table type_nested 2.945 s 1.302
2023-01-20 00:57 Python dataframe-to-table chi_traffic_2020_Q1 20.833 s 1.552
2023-01-20 00:58 Python dataframe-to-table type_dict 0.011 s -1.686
2023-01-20 00:58 Python dataframe-to-table type_floats 0.010 s 0.192
2023-01-20 00:58 Python dataset-filter nyctaxi_2010-01 1.028 s -0.287
2023-01-20 01:02 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 82.320 s -0.122
2023-01-20 01:07 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 85.026 s -0.514
2023-01-20 01:18 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.038 s 0.238
2023-01-20 01:18 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.231 s 0.094
2023-01-20 01:18 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.036 s 0.238
2023-01-20 01:19 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.394
2023-01-20 01:20 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.256 s 2.324
2023-01-20 01:18 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.304 s 1.128
2023-01-20 01:19 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.910 s 0.947
2023-01-20 01:17 Python dataset-read async=True, nyctaxi_multi_ipc_s3 214.944 s 1.153
2023-01-20 01:18 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.190 s 0.146
2023-01-20 01:18 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.127 s 0.366
2023-01-20 01:18 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.601
2023-01-20 01:18 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.678 s 0.225
2023-01-20 01:23 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.154 s -1.061
2023-01-20 01:17 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.338 s -0.006
2023-01-20 01:19 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.995
2023-01-20 01:23 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.051 s 1.058
2023-01-20 01:18 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.311 s 0.109
2023-01-20 01:19 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.730 s 2.304
2023-01-20 01:23 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.150 s -0.176
2023-01-20 01:18 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.177 s -0.530
2023-01-20 01:19 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 1.082
2023-01-20 01:36 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.411 s -0.335
2023-01-20 01:18 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.203 s 0.060
2023-01-20 01:31 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s -1.300
2023-01-20 01:31 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.834 s 2.319
2023-01-20 01:31 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 73.279 s 2.315
2023-01-20 01:32 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.224 s 1.489
2023-01-20 01:45 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.628 s 0.056
2023-01-20 01:46 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.983 s -0.017
2023-01-20 01:31 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.284 s 0.111
2023-01-20 01:31 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.006 s 0.403
2023-01-20 01:32 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.225 s 0.930
2023-01-20 01:47 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.593 s -0.202
2023-01-20 01:50 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.304 s -0.136
2023-01-20 01:31 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.031
2023-01-20 01:46 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.309 s -2.108
2023-01-20 01:46 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.994 s -0.154
2023-01-20 01:47 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.575 s 0.357
2023-01-20 01:47 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.310 s 0.570
2023-01-20 01:51 Python file-write lz4, feather, table, fanniemae_2016Q4 1.866 s -0.195
2023-01-20 01:45 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.646 s 0.024
2023-01-20 01:46 Python file-read lz4, feather, table, fanniemae_2016Q4 0.806 s 0.490
2023-01-20 01:52 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.832 s 0.016
2023-01-20 01:50 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.251 s 0.025
2023-01-20 01:54 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.173 s 0.238
2023-01-20 01:32 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.373 s 2.358
2023-01-20 01:45 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 83.111 s 2.334
2023-01-20 01:54 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.162 s -0.305
2023-01-20 01:54 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.231 s -0.366
2023-01-20 01:36 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.452 s 0.466
2023-01-20 01:36 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.407 s 0.116
2023-01-20 01:49 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.745 s 0.041
2023-01-20 01:53 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.693 s 0.176
2023-01-20 01:45 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.308 s 0.302
2023-01-20 01:46 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.726 s 0.012
2023-01-20 01:46 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.943 s -0.069
2023-01-20 01:54 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.704 s -0.052
2023-01-20 01:54 Python file-write lz4, feather, table, nyctaxi_2010-01 1.835 s -0.542
2023-01-20 01:45 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.523 s -0.911
2023-01-20 01:45 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.515 s -0.782
2023-01-20 01:46 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.950 s -0.227
2023-01-20 01:52 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.898 s -0.070
2023-01-20 01:53 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.299 s 0.099
2023-01-20 01:46 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.929 s 0.309
2023-01-20 01:48 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.096 s -0.038
2023-01-20 01:51 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.300 s -0.280
2023-01-20 01:47 Python file-read lz4, feather, table, nyctaxi_2010-01 0.677 s 0.243
2023-01-20 01:54 Python wide-dataframe use_legacy_dataset=false 0.514 s 0.233
2023-01-20 01:54 Python wide-dataframe use_legacy_dataset=true 0.377 s 0.147
2023-01-20 02:03 R dataframe-to-table chi_traffic_2020_Q1, R 4.382 s -0.820
2023-01-20 02:03 R dataframe-to-table type_strings, R 0.535 s -0.053
2023-01-20 02:03 R dataframe-to-table type_integers, R 0.010 s -0.023
2023-01-20 02:04 R dataframe-to-table type_nested, R 0.573 s 0.194
2023-01-20 02:03 R dataframe-to-table type_dict, R 0.060 s -0.535
2023-01-20 02:04 R dataframe-to-table type_floats, R 0.013 s 0.034
2023-01-20 02:04 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.602 s -1.618
2023-01-20 02:04 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.342 s -1.403
2023-01-20 02:04 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.349 s -1.756
2023-01-20 02:05 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.596 s -1.231
2023-01-20 02:05 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.574 s 0.144
2023-01-20 02:06 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.578 s -0.723
2023-01-20 02:05 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.315 s 0.200
2023-01-20 02:05 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.591 s 0.241
2023-01-20 02:05 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.846 s 0.266
2023-01-20 02:06 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.576 s -0.577
2023-01-20 02:06 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.928 s -0.664
2023-01-20 02:06 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.930 s -0.796
2023-01-20 02:06 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.818 s 0.232
2023-01-20 02:07 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.909 s 0.167
2023-01-20 02:06 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.214 s 0.244
2023-01-20 02:07 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.581 s 0.196
2023-01-20 02:08 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.712 s -0.005
2023-01-20 02:10 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.651 s 0.126
2023-01-20 02:10 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.124 s 0.015
2023-01-20 02:12 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.150 s -0.078
2023-01-20 02:13 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.963 s -0.585
2023-01-20 02:14 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.018 s 0.366
2023-01-20 02:15 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.493 s -0.331
2023-01-20 02:16 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.484 s 0.132
2023-01-20 02:17 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.961 s -0.184
2023-01-20 02:19 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.777 s -0.135
2023-01-20 02:26 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.370 s -2.994
2023-01-20 02:27 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.837 s -0.308
2023-01-20 02:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.361 s -0.414
2023-01-20 02:33 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.676 s 0.433
2023-01-20 02:33 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.216 s -0.436
2023-01-20 02:34 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.248 s -0.317
2023-01-20 02:24 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.087 s -0.827
2023-01-20 02:24 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.567 s -0.285
2023-01-20 02:25 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.254 s -3.527
2023-01-20 02:26 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.280 s -0.471
2023-01-20 02:28 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.278 s -0.468
2023-01-20 02:29 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.310 s -0.069
2023-01-20 02:32 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.275 s -0.949
2023-01-20 02:32 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.332 s -1.053
2023-01-20 02:26 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.269 s -4.027
2023-01-20 02:31 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.193 s -0.018
2023-01-20 02:32 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.271 s -1.517
2023-01-20 02:33 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.641 s -0.466
2023-01-20 02:36 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.671 s -0.091
2023-01-20 02:25 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.624 s -1.732
2023-01-20 02:25 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.377 s -4.319
2023-01-20 02:29 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.312 s -0.977
2023-01-20 02:30 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.904 s -0.613
2023-01-20 02:30 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.203 s -0.051
2023-01-20 02:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.324 s -0.534
2023-01-20 02:34 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.183 s -0.402
2023-01-20 02:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.304 s -0.390
2023-01-20 02:35 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.386 s -0.124
2023-01-20 02:21 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.312 s -0.575
2023-01-20 02:28 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.350 s -1.134
2023-01-20 02:29 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.243 s -0.463
2023-01-20 02:30 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.205 s -0.051
2023-01-20 02:31 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.276 s -0.658
2023-01-20 02:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.654 s -0.544
2023-01-20 02:35 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.267 s -0.120
2023-01-20 02:23 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.470 s 0.454
2023-01-20 02:24 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.612 s -1.259
2023-01-20 02:20 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.656 s 0.171
2023-01-20 02:22 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.189 s -0.949
2023-01-20 02:28 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.364 s -0.911
2023-01-20 02:28 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.448 s -0.737
2023-01-20 02:31 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.334 s 0.045
2023-01-20 02:21 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.734 s -0.128
2023-01-20 02:25 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.255 s -0.683
2023-01-20 02:27 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.350 s -1.857
2023-01-20 02:28 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.080 s -1.007
2023-01-20 02:29 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.594 s -0.169
2023-01-20 02:30 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.552 s -0.223
2023-01-20 02:30 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.248 s -0.054
2023-01-20 02:26 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.595 s -0.557
2023-01-20 02:27 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.294 s -13.382
2023-01-20 02:27 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.304 s -1.472
2023-01-20 02:34 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.357 s -0.208
2023-01-20 02:27 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.009 s -1.356
2023-01-20 02:30 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.238 s 0.049
2023-01-20 02:34 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.165 s -0.181
2023-01-20 02:35 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.351 s -0.067
2023-01-20 02:28 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.680 s -1.639
2023-01-20 02:28 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.240 s -1.493
2023-01-20 02:31 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.916 s -0.191
2023-01-20 02:33 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.167 s -0.206
2023-01-20 02:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.363 s -0.380
2023-01-20 02:34 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.515 s -0.251
2023-01-20 02:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.306 s -0.517
2023-01-20 02:36 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.799 s -0.853
2023-01-20 02:36 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.634 s -0.090
2023-01-20 02:37 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.410 s -0.297
2023-01-20 02:37 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.353 s -1.065
2023-01-20 02:37 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.443 s -0.371
2023-01-20 02:38 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.633 s -2.172
2023-01-20 02:37 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.358 s -1.105
2023-01-20 02:37 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.389 s -1.211
2023-01-20 02:37 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.732 s -0.395
2023-01-20 02:38 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.778 s -0.160
2023-01-20 02:39 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.306 s -0.538
2023-01-20 02:39 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.453 s -1.087
2023-01-20 02:38 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.281 s -0.464
2023-01-20 02:38 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.335 s -0.217
2023-01-20 02:39 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.383 s -0.163
2023-01-20 02:39 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.775 s -0.041
2023-01-20 02:40 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.309 s -0.114
2023-01-20 02:40 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.978 s -1.280
2023-01-20 02:40 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.144 s -0.078
2023-01-20 02:40 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.273 s -0.710
2023-01-20 02:41 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.337 s -3.035
2023-01-20 02:40 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.269 s -1.103
2023-01-20 02:41 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.347 s -0.293
2023-01-20 02:41 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.659 s -0.376
2023-01-20 02:42 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.218 s -0.392
2023-01-20 02:41 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.885 s -1.439
2023-01-20 02:42 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.742 s 0.016
2023-01-20 02:42 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.271 s -0.255
2023-01-20 02:43 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.878 s -0.886
2023-01-20 02:42 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.242 s -0.588
2023-01-20 02:43 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.550 s -0.439
2023-01-20 02:43 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.266 s -0.432
2023-01-20 02:42 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.312 s -0.175
2023-01-20 02:42 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.335 s -0.498
2023-01-20 02:43 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.219 s -0.457
2023-01-20 02:44 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.361 s -6.127
2023-01-20 02:44 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.338 s -3.867
2023-01-20 02:44 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.940 s -0.625
2023-01-20 02:44 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.480 s -5.941
2023-01-20 02:44 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.515 s -2.252
2023-01-20 02:45 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.699 s -1.220
2023-01-20 02:46 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.193 s -0.365
2023-01-20 02:46 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.616 s -0.561
2023-01-20 02:46 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.246 s -0.187
2023-01-20 02:46 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.340 s -0.617
2023-01-20 02:46 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.617 s -0.898
2023-01-20 02:46 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.869 s -0.228
2023-01-20 02:46 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.435 s -0.317
2023-01-20 02:47 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.525 s -0.146
2023-01-20 02:47 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.455 s -1.213
2023-01-20 02:48 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.278 s -0.046
2023-01-20 02:47 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.226 s -0.167
2023-01-20 02:48 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.250 s -0.128
2023-01-20 02:48 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.450 s -0.383
2023-01-20 02:48 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.346 s -0.160
2023-01-20 02:48 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.956 s -0.278
2023-01-20 02:49 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 6.103 s -0.563
2023-01-20 02:49 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.216 s -0.043
2023-01-20 02:49 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.608 s -1.055
2023-01-20 02:49 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.260 s 0.087
2023-01-20 02:50 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.292 s 0.069
2023-01-20 02:50 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.218 s -0.047
2023-01-20 02:50 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.250 s -0.132
2023-01-20 02:50 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.593 s 0.003
2023-01-20 02:51 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.630 s -0.659
2023-01-20 02:51 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.201 s -0.007
2023-01-20 02:51 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.558 s 0.426
2023-01-20 02:51 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.249 s -0.060
2023-01-20 02:51 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.227 s -0.103
2023-01-20 02:52 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.329 s -0.064
2023-01-20 02:51 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.296 s -0.168
2023-01-20 02:52 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.537 s -0.027
2023-01-20 02:52 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.232 s -0.355
2023-01-20 02:52 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.111 s -0.031
2023-01-20 02:52 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.889 s -0.118
2023-01-20 02:53 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.283 s -0.202
2023-01-20 02:53 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.236 s -0.523
2023-01-20 02:53 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.275 s -0.656
2023-01-20 02:53 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 1.013 s -0.551
2023-01-20 02:53 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.336 s -0.158
2023-01-20 02:54 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.201 s -0.240
2023-01-20 02:54 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.682 s -0.940
2023-01-20 02:54 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.982 s -0.202
2023-01-20 02:54 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.250 s -0.001
2023-01-20 02:55 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.217 s -0.181
2023-01-20 02:55 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.273 s 0.012
2023-01-20 02:55 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.412 s -0.317
2023-01-20 02:56 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.468 s -0.354
2023-01-20 02:55 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.539 s 0.132
2023-01-20 02:56 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.541 s -2.628
2023-01-20 02:56 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.364 s -7.381
2023-01-20 02:57 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.496 s -5.210
2023-01-20 02:57 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.454 s -5.191
2023-01-20 02:57 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.355 s -0.927
2023-01-20 02:58 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.689 s -1.905
2023-01-20 02:57 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.459 s -0.861
2023-01-20 02:57 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.905 s -2.991
2023-01-20 02:59 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.473 s -0.999
2023-01-20 02:59 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.273 s -1.093
2023-01-20 02:59 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.386 s -0.765
2023-01-20 02:59 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.306 s -1.732
2023-01-20 02:59 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.336 s -0.625
2023-01-20 02:59 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.275 s -1.387
2023-01-20 03:00 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.619 s -2.065
2023-01-20 03:00 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.981 s -0.383
2023-01-20 03:01 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.419 s -6.652
2023-01-20 03:01 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.119 s -0.226
2023-01-20 03:01 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.478 s -1.721
2023-01-20 03:01 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.818 s -1.097
2023-01-20 03:02 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.884 s -0.124
2023-01-20 03:01 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.755 s -3.100
2023-01-20 03:02 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.187 s -1.140
2023-01-20 03:04 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 29.951 s -0.297
2023-01-20 03:06 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.272 s -7.218
2023-01-20 03:06 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 32.508 s 0.707
2023-01-20 03:07 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.298 s -1.260
2023-01-20 03:08 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.361 s -0.372
2023-01-20 03:07 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.234 s -0.409
2023-01-20 03:08 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.317 s -0.572
2023-01-20 03:07 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.354 s -4.562
2023-01-20 03:07 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.263 s -4.407
2023-01-20 03:07 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.464 s -0.331
2023-01-20 03:16 JavaScript Iterate Vector uint8Array 0.002 s 0.481
2023-01-20 03:16 JavaScript Iterate Vector dictionary 0.004 s 0.461
2023-01-20 03:16 JavaScript Iterate Vector uint64Array 0.004 s 0.757
2023-01-20 03:16 JavaScript Iterate Vector uint32Array 0.002 s 0.529
2023-01-20 03:16 JavaScript vectorFromArray dictionary 0.017 s 0.165
2023-01-20 03:16 JavaScript Iterate Vector booleans 0.004 s 0.950
2023-01-20 03:17 JavaScript Table 1,000,000, tracks 0.275 s 0.097
2023-01-20 03:16 JavaScript Iterate Vector int16Array 0.002 s 0.548
2023-01-20 03:16 JavaScript Iterate Vector float64Array 0.002 s 0.286
2023-01-20 03:17 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.099
2023-01-20 03:16 JavaScript Iterate Vector int32Array 0.002 s 0.635
2023-01-20 03:16 JavaScript Iterate Vector float32Array 0.002 s 0.731
2023-01-20 03:16 JavaScript Spread Vector dictionary 0.010 s 0.102
2023-01-20 03:16 JavaScript toArray Vector uint8Array
2023-01-20 03:16 JavaScript Iterate Vector uint16Array 0.002 s 0.347
2023-01-20 03:16 JavaScript Spread Vector float64Array 0.008 s -0.293
2023-01-20 03:16 JavaScript Spread Vector booleans 0.010 s 0.786
2023-01-20 03:16 JavaScript Iterate Vector int8Array 0.002 s 1.103
2023-01-20 03:16 JavaScript Spread Vector int8Array 0.006 s 0.390
2023-01-20 03:16 JavaScript vectorFromArray numbers 0.016 s -0.114
2023-01-20 03:16 JavaScript Iterate Vector string 0.124 s 1.238
2023-01-20 03:16 JavaScript Spread Vector uint64Array 0.012 s 0.294
2023-01-20 03:16 JavaScript Spread Vector int16Array 0.006 s 0.672
2023-01-20 03:16 JavaScript toArray Vector numbers
2023-01-20 03:16 JavaScript vectorFromArray booleans 0.017 s 0.724
2023-01-20 03:16 JavaScript Iterate Vector numbers 0.002 s 0.590
2023-01-20 03:17 JavaScript get Vector int8Array 0.003 s 0.205
2023-01-20 03:17 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.735
2023-01-20 03:17 JavaScript Table tracks, 1,000,000 0.050 s 0.409
2023-01-20 03:16 JavaScript Iterate Vector int64Array 0.004 s 1.032
2023-01-20 03:16 JavaScript toArray Vector int64Array
2023-01-20 03:16 JavaScript toArray Vector float64Array
2023-01-20 03:16 JavaScript toArray Vector booleans 0.010 s 0.626
2023-01-20 03:16 JavaScript toArray Vector string 0.144 s 0.987
2023-01-20 03:17 JavaScript Table tracks, 1,000,000 0.269 s 0.065
2023-01-20 03:16 JavaScript Spread Vector uint8Array 0.006 s 0.576
2023-01-20 03:16 JavaScript Spread Vector uint32Array 0.007 s 0.429
2023-01-20 03:16 JavaScript Spread Vector int32Array 0.007 s 0.147
2023-01-20 03:16 JavaScript Spread Vector numbers 0.008 s 0.682
2023-01-20 03:17 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.611
2023-01-20 03:16 JavaScript Spread Vector uint16Array 0.006 s 0.124
2023-01-20 03:16 JavaScript Spread Vector string 0.143 s 1.329
2023-01-20 03:17 JavaScript get Vector uint64Array 0.003 s 0.905
2023-01-20 03:17 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.324
2023-01-20 03:16 JavaScript Spread Vector int64Array 0.012 s 0.571
2023-01-20 03:16 JavaScript toArray Vector int16Array
2023-01-20 03:16 JavaScript get Vector uint16Array 0.003 s 0.055
2023-01-20 03:17 JavaScript get Vector int64Array 0.003 s 0.318
2023-01-20 03:17 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.172
2023-01-20 03:16 JavaScript Spread Vector float32Array 0.008 s 0.215
2023-01-20 03:17 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.451
2023-01-20 03:17 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-20 03:16 JavaScript toArray Vector uint16Array
2023-01-20 03:17 JavaScript get Vector int16Array 0.003 s -0.017
2023-01-20 03:17 JavaScript get Vector float64Array 0.002 s -0.242
2023-01-20 03:17 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.985
2023-01-20 03:17 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.090
2023-01-20 03:16 JavaScript toArray Vector uint32Array
2023-01-20 03:16 JavaScript toArray Vector int8Array
2023-01-20 03:16 JavaScript toArray Vector int32Array
2023-01-20 03:16 JavaScript toArray Vector float32Array
2023-01-20 03:16 JavaScript toArray Vector dictionary 0.010 s 0.195
2023-01-20 03:16 JavaScript toArray Vector uint64Array
2023-01-20 03:17 JavaScript get Vector string 0.124 s 0.832
2023-01-20 03:17 JavaScript Parse write recordBatches, tracks 0.002 s -2.367
2023-01-20 03:17 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.038 s 0.984
2023-01-20 03:17 JavaScript Table tracks, 1,000,000 0.094 s 0.882
2023-01-20 03:16 JavaScript get Vector uint8Array 0.003 s -0.146
2023-01-20 03:17 JavaScript get Vector int32Array 0.003 s -0.052
2023-01-20 03:17 JavaScript get Vector float32Array 0.002 s 0.462
2023-01-20 03:17 JavaScript get Vector numbers 0.002 s -0.149
2023-01-20 03:17 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.185 s 1.141
2023-01-20 03:17 JavaScript get Vector uint32Array 0.003 s -0.137
2023-01-20 03:17 JavaScript get Vector dictionary 0.002 s 0.678
2023-01-20 03:17 JavaScript Parse read recordBatches, tracks 0.000 s -2.981
2023-01-20 03:17 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.335
2023-01-20 03:17 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.185
2023-01-20 03:17 JavaScript get Vector booleans 0.002 s 1.115
2023-01-20 03:17 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.563
2023-01-20 03:17 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-20 03:17 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.617
2023-01-20 03:17 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-20 03:17 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -0.375
2023-01-20 03:17 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s 0.797
2023-01-20 03:17 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.045
2023-01-20 03:17 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-20 03:17 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.191 s -1.511
2023-01-20 03:17 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.392