Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-19 10:39 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.246 s 0.186
2023-01-19 10:39 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.774 s 0.724
2023-01-19 10:41 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.435 s 0.407
2023-01-19 10:42 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.316 s 1.259
2023-01-19 10:40 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.250 s -1.522
2023-01-19 10:45 Python dataframe-to-table type_nested 2.958 s 0.456
2023-01-19 10:48 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 70.358 s 1.136
2023-01-19 10:44 Python dataframe-to-table type_floats 0.010 s 0.180
2023-01-19 10:44 Python dataframe-to-table type_dict 0.011 s -0.183
2023-01-19 10:41 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.224 s -1.511
2023-01-19 10:44 Python dataframe-to-table type_strings 0.425 s 0.828
2023-01-19 10:44 Python dataframe-to-table type_integers 0.010 s 0.521
2023-01-19 10:45 Python dataset-filter nyctaxi_2010-01 1.022 s -0.222
2023-01-19 10:41 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.136 s 0.027
2023-01-19 10:42 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.460 s 1.087
2023-01-19 10:44 Python dataframe-to-table chi_traffic_2020_Q1 20.886 s 1.305
2023-01-19 11:04 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.295 s 0.253
2023-01-19 11:05 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.022 s 0.936
2023-01-19 11:06 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.256 s 3.063
2023-01-19 11:04 Python dataset-read async=True, nyctaxi_multi_ipc_s3 216.683 s 0.901
2023-01-19 11:05 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s -1.664
2023-01-19 11:09 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.418 s -1.627
2023-01-19 10:53 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 84.512 s -0.225
2023-01-19 11:05 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.307 s -1.680
2023-01-19 11:05 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.944 s -1.668
2023-01-19 11:10 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.159 s -3.486
2023-01-19 11:04 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.864 s -4.203
2023-01-19 11:04 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.031 s 0.273
2023-01-19 11:05 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.662 s 0.276
2023-01-19 11:05 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.199 s 0.127
2023-01-19 11:05 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.279
2023-01-19 11:17 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.188
2023-01-19 11:04 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.291 s 0.303
2023-01-19 11:04 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.886 s -4.400
2023-01-19 11:04 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.020 s 0.305
2023-01-19 11:05 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.130 s 0.197
2023-01-19 11:05 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.730 s 3.023
2023-01-19 11:18 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.834 s 3.140
2023-01-19 11:05 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.163 s 0.082
2023-01-19 11:05 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.824
2023-01-19 11:17 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 73.267 s 3.072
2023-01-19 11:10 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.149 s 0.154
2023-01-19 11:32 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.503 s -0.229
2023-01-19 11:38 Python file-write lz4, feather, table, fanniemae_2016Q4 1.841 s 0.097
2023-01-19 11:41 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.237 s -0.327
2023-01-19 11:41 Python wide-dataframe use_legacy_dataset=true 0.377 s 0.256
2023-01-19 11:18 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.225 s 0.799
2023-01-19 11:32 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.324 s 0.231
2023-01-19 11:39 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.444 s -0.889
2023-01-19 11:17 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.291 s -1.752
2023-01-19 11:22 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 31.195 s -1.696
2023-01-19 11:32 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.499 s -0.201
2023-01-19 11:34 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.725 s -0.999
2023-01-19 11:18 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.075 s -1.653
2023-01-19 11:31 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 83.119 s 3.086
2023-01-19 11:38 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.937 s -0.382
2023-01-19 11:32 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.726 s -0.047
2023-01-19 11:33 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.312 s 0.564
2023-01-19 11:37 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.571 s -1.452
2023-01-19 11:38 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.272 s -0.182
2023-01-19 11:50 R dataframe-to-table type_strings, R 0.534 s 0.202
2023-01-19 11:50 R dataframe-to-table type_dict, R 0.062 s -0.860
2023-01-19 11:17 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 0.947
2023-01-19 11:19 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.373 s 3.125
2023-01-19 11:32 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.618 s 0.152
2023-01-19 11:33 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.304 s -2.461
2023-01-19 11:33 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.953 s -0.255
2023-01-19 11:33 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.574 s 0.363
2023-01-19 11:50 R dataframe-to-table type_integers, R 0.010 s 0.512
2023-01-19 11:50 R dataframe-to-table type_nested, R 0.574 s 0.042
2023-01-19 11:53 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.815 s 0.242
2023-01-19 11:53 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.908 s 0.144
2023-01-19 12:05 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.803 s -0.448
2023-01-19 11:18 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.475
2023-01-19 11:22 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.410 s -0.885
2023-01-19 11:23 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.409 s 0.137
2023-01-19 11:31 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.638 s 0.098
2023-01-19 11:33 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.964 s 0.275
2023-01-19 11:33 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.992 s -0.191
2023-01-19 11:33 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.935 s 0.272
2023-01-19 11:36 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.982 s -1.189
2023-01-19 11:37 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.377 s -0.206
2023-01-19 11:39 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.952 s -0.780
2023-01-19 11:40 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.840 s -0.859
2023-01-19 11:52 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.612 s 0.109
2023-01-19 11:59 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.356 s -1.169
2023-01-19 12:11 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.084 s -0.712
2023-01-19 12:13 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -1.352
2023-01-19 12:14 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.336 s 0.082
2023-01-19 12:14 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.147
2023-01-19 11:32 Python file-read lz4, feather, table, fanniemae_2016Q4 0.810 s 0.364
2023-01-19 11:33 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.930 s 0.040
2023-01-19 11:33 Python file-read lz4, feather, table, nyctaxi_2010-01 0.673 s 0.290
2023-01-19 11:57 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.364 s -1.210
2023-01-19 11:35 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.412 s -1.488
2023-01-19 11:40 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.733 s -0.091
2023-01-19 11:49 R dataframe-to-table chi_traffic_2020_Q1, R 4.375 s -0.828
2023-01-19 11:51 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.580 s -0.766
2023-01-19 11:52 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.917 s -0.340
2023-01-19 11:53 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.216 s 0.229
2023-01-19 12:00 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.985 s -4.402
2023-01-19 12:11 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.570 s -0.511
2023-01-19 12:12 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.590 s -0.163
2023-01-19 12:13 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 4.072 s -1.917
2023-01-19 12:14 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.075 s -0.728
2023-01-19 12:18 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.904 s 0.722
2023-01-19 12:19 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.319 s 0.316
2023-01-19 12:20 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.155
2023-01-19 12:20 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.178 s 0.251
2023-01-19 12:21 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.265
2023-01-19 11:41 Python wide-dataframe use_legacy_dataset=false 0.511 s 0.565
2023-01-19 11:51 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.585 s -0.842
2023-01-19 11:54 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.956 s -1.236
2023-01-19 11:56 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.870 s -1.035
2023-01-19 12:02 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.494 s -0.415
2023-01-19 11:51 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.324 s -0.706
2023-01-19 11:51 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.313 s 0.230
2023-01-19 11:53 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.582 s 0.190
2023-01-19 12:01 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.018 s 0.415
2023-01-19 12:04 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.998 s -0.613
2023-01-19 12:11 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.251 s 0.246
2023-01-19 12:15 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.318 s -4.395
2023-01-19 12:18 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.192 s 0.069
2023-01-19 12:20 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.262
2023-01-19 11:40 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.305 s -0.713
2023-01-19 11:41 Python file-write lz4, feather, table, nyctaxi_2010-01 1.757 s 0.147
2023-01-19 11:51 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.569 s 0.201
2023-01-19 11:53 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.920 s -0.458
2023-01-19 12:13 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.335 s -0.032
2023-01-19 12:14 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.348 s 0.159
2023-01-19 12:15 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.357 s -4.655
2023-01-19 12:18 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.266 s 0.153
2023-01-19 12:20 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.160 s 0.210
2023-01-19 11:41 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.131 s -0.094
2023-01-19 11:50 R dataframe-to-table type_floats, R 0.013 s 0.332
2023-01-19 11:52 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.571 s -0.443
2023-01-19 12:06 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.717 s -0.485
2023-01-19 12:08 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.314 s -1.212
2023-01-19 12:17 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.242 s 0.272
2023-01-19 12:19 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.644 s -0.031
2023-01-19 12:20 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.738 s -0.430
2023-01-19 12:22 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.374 s 0.285
2023-01-19 11:52 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 1.552 s -4.357
2023-01-19 11:52 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.640 s -2.353
2023-01-19 12:03 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.475 s 0.376
2023-01-19 12:12 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.239 s 0.254
2023-01-19 12:22 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.293 s 0.261
2023-01-19 11:51 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.321 s -0.383
2023-01-19 12:07 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.765 s -0.509
2023-01-19 12:16 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.882 s 0.866
2023-01-19 12:17 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.201 s 0.310
2023-01-19 12:22 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.339 s 0.304
2023-01-19 12:09 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.189 s -1.059
2023-01-19 12:10 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.469 s 0.772
2023-01-19 12:11 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.586 s -0.453
2023-01-19 12:11 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.611 s -0.794
2023-01-19 12:12 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.281 s 0.188
2023-01-19 12:14 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.433 s 0.133
2023-01-19 12:15 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.442 s -4.663
2023-01-19 12:16 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.588 s 0.145
2023-01-19 12:16 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.559 s -0.121
2023-01-19 12:17 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.232 s 0.338
2023-01-19 12:17 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.268 s 0.475
2023-01-19 12:18 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.262 s 0.089
2023-01-19 12:19 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.720 s -8.204
2023-01-19 12:21 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.349 s 0.476
2023-01-19 12:22 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.351 s 0.225
2023-01-19 12:11 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.205 s -0.150
2023-01-19 12:12 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.201 s 0.183
2023-01-19 12:12 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.274 s 0.109
2023-01-19 12:13 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.007 s -0.732
2023-01-19 12:13 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.291 s 0.016
2023-01-19 12:14 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.670 s -0.890
2023-01-19 12:15 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.316 s -0.956
2023-01-19 12:16 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.335
2023-01-19 12:17 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.326 s 0.377
2023-01-19 12:18 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.313 s 0.205
2023-01-19 12:23 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.783 s 0.189
2023-01-19 12:19 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.351 s 0.166
2023-01-19 12:20 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.201 s 0.210
2023-01-19 12:21 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.508 s 0.122
2023-01-19 12:21 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.273 s -0.146
2023-01-19 12:22 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.664 s 0.109
2023-01-19 12:23 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.637 s -0.122
2023-01-19 12:23 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.395 s 0.250
2023-01-19 12:24 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.370 s 0.184
2023-01-19 12:23 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.335 s 0.179
2023-01-19 12:24 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.429 s 0.192
2023-01-19 12:23 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.340 s 0.170
2023-01-19 12:24 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.716 s 0.191
2023-01-19 12:25 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.767 s -0.014
2023-01-19 12:25 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.372 s 0.246
2023-01-19 12:24 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.618 s -0.206
2023-01-19 12:25 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.271 s 0.273
2023-01-19 12:25 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.297 s 0.209
2023-01-19 12:26 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.442 s 0.066
2023-01-19 12:25 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.323 s 0.296
2023-01-19 12:27 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.152 s -0.146
2023-01-19 12:26 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.773 s 0.073
2023-01-19 12:27 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.299 s 0.291
2023-01-19 12:26 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.960 s 0.094
2023-01-19 12:27 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.256 s 0.142
2023-01-19 12:27 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.259 s 0.245
2023-01-19 12:27 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.321 s 0.122
2023-01-19 12:28 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.868 s 0.861
2023-01-19 12:27 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.335 s 0.239
2023-01-19 12:27 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.653 s 0.098
2023-01-19 12:29 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.165
2023-01-19 12:29 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.303 s 0.220
2023-01-19 12:28 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.755 s -0.135
2023-01-19 12:29 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.540 s -0.043
2023-01-19 12:28 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.210 s 0.157
2023-01-19 12:29 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.231 s 0.144
2023-01-19 12:29 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.866 s 0.282
2023-01-19 12:30 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.303 s 0.082
2023-01-19 12:29 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.328 s 0.295
2023-01-19 12:30 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.210 s 0.112
2023-01-19 12:30 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.267 s -0.503
2023-01-19 12:30 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.256 s 0.151
2023-01-19 12:30 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.367 s 0.050
2023-01-19 12:30 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.500 s -1.244
2023-01-19 12:31 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.915 s -0.269
2023-01-19 12:31 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.696 s -1.332
2023-01-19 12:32 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.227 s -2.400
2023-01-19 12:32 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 7.607 s -3.608
2023-01-19 12:33 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.613 s -0.769
2023-01-19 12:32 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.334 s -0.076
2023-01-19 12:32 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.240 s 0.048
2023-01-19 12:32 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.428 s 0.035
2023-01-19 12:33 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.462 s -1.465
2023-01-19 12:33 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.861 s -0.053
2023-01-19 12:34 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.545 s -0.368
2023-01-19 12:34 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.334 s 0.263
2023-01-19 12:34 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.217 s 0.216
2023-01-19 12:34 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.266 s 0.298
2023-01-19 12:34 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.237
2023-01-19 12:34 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.937 s 0.079
2023-01-19 12:34 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.445 s -0.094
2023-01-19 12:35 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.607 s -1.115
2023-01-19 12:36 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.337
2023-01-19 12:35 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 6.027 s -0.335
2023-01-19 12:36 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.209 s 0.306
2023-01-19 12:36 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.421 s -3.629
2023-01-19 12:36 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.268 s -2.089
2023-01-19 12:36 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.307 s -3.116
2023-01-19 12:37 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.643 s -1.413
2023-01-19 12:37 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.638 s -0.614
2023-01-19 12:37 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.616 s 0.099
2023-01-19 12:38 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.196 s 0.219
2023-01-19 12:38 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.285 s 0.203
2023-01-19 12:38 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.237 s 0.282
2023-01-19 12:38 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.324 s 0.256
2023-01-19 12:38 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.223 s 0.149
2023-01-19 12:39 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.889 s -0.154
2023-01-19 12:38 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.521 s 0.357
2023-01-19 12:39 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.267 s 0.258
2023-01-19 12:39 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.083 s 0.151
2023-01-19 12:39 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.221 s 0.214
2023-01-19 12:39 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.216 s 0.252
2023-01-19 12:40 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.260 s 0.177
2023-01-19 12:39 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.320 s 0.325
2023-01-19 12:40 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 1.009 s -0.474
2023-01-19 12:40 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.669 s -0.023
2023-01-19 12:41 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.194 s 0.244
2023-01-19 12:41 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.944 s -0.149
2023-01-19 12:41 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.208 s 0.279
2023-01-19 12:41 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.263 s 0.276
2023-01-19 12:41 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.240 s 0.311
2023-01-19 12:41 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.408 s -0.034
2023-01-19 12:42 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.531 s 0.385
2023-01-19 12:42 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.298 s -0.101
2023-01-19 12:42 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.462 s -0.205
2023-01-19 12:43 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.327 s 0.176
2023-01-19 12:43 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s -0.030
2023-01-19 12:43 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.894 s -1.113
2023-01-19 12:43 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.443 s 0.112
2023-01-19 12:43 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.442 s -0.120
2023-01-19 12:43 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.329 s 0.020
2023-01-19 12:44 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.663 s -1.097
2023-01-19 12:45 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.470 s -1.137
2023-01-19 12:45 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.257 s 0.074
2023-01-19 12:46 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.288 s -0.005
2023-01-19 12:45 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.370 s 0.253
2023-01-19 12:45 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.320 s 0.153
2023-01-19 12:45 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.258 s 0.057
2023-01-19 12:46 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.986 s -0.570
2023-01-19 12:46 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.602 s 0.305
2023-01-19 12:47 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.105 s -0.223
2023-01-19 12:47 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.396 s -0.058
2023-01-19 12:47 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.733 s -0.243
2023-01-19 12:47 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.796 s 0.002
2023-01-19 12:47 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.453 s -0.067
2023-01-19 12:48 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.883 s -0.077
2023-01-19 12:48 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.153 s -0.286
2023-01-19 12:50 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 29.933 s -0.225
2023-01-19 12:52 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.238 s -1.577
2023-01-19 12:52 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.199 s 0.061
2023-01-19 12:53 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.227 s 0.118
2023-01-19 12:53 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.204 s 0.144
2023-01-19 12:53 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.242 s 0.229
2023-01-19 12:53 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.261 s 0.191
2023-01-19 12:53 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.311 s -0.230
2023-01-19 12:53 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.454 s 0.023
2023-01-19 12:54 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.349 s -0.528
2023-01-19 13:02 JavaScript Iterate Vector string 0.126 s -0.185
2023-01-19 13:02 JavaScript Spread Vector uint8Array 0.006 s 0.575
2023-01-19 13:02 JavaScript Iterate Vector uint8Array 0.002 s -0.044
2023-01-19 13:02 JavaScript Iterate Vector int16Array 0.002 s 0.596
2023-01-19 13:02 JavaScript Iterate Vector float64Array 0.002 s 0.551
2023-01-19 13:02 JavaScript Iterate Vector uint32Array 0.002 s 0.644
2023-01-19 13:02 JavaScript Iterate Vector int64Array 0.004 s 1.063
2023-01-19 13:02 JavaScript toArray Vector int8Array
2023-01-19 13:02 JavaScript Iterate Vector uint64Array 0.004 s 0.908
2023-01-19 13:02 JavaScript Iterate Vector int8Array 0.002 s 0.333
2023-01-19 13:02 JavaScript Spread Vector float32Array 0.008 s -0.004
2023-01-19 13:02 JavaScript Spread Vector booleans 0.010 s 0.632
2023-01-19 13:02 JavaScript Spread Vector dictionary 0.010 s 0.871
2023-01-19 13:02 JavaScript toArray Vector uint8Array
2023-01-19 13:02 JavaScript Iterate Vector uint16Array 0.002 s 0.750
2023-01-19 13:02 JavaScript toArray Vector int32Array
2023-01-19 13:02 JavaScript toArray Vector float64Array
2023-01-19 13:02 JavaScript toArray Vector dictionary 0.010 s 0.659
2023-01-19 13:02 JavaScript Spread Vector int64Array 0.012 s 0.960
2023-01-19 13:02 JavaScript Spread Vector numbers 0.008 s -0.006
2023-01-19 13:02 JavaScript get Vector uint8Array 0.003 s 0.803
2023-01-19 13:02 JavaScript vectorFromArray numbers 0.016 s 0.474
2023-01-19 13:02 JavaScript vectorFromArray booleans 0.017 s 0.622
2023-01-19 13:02 JavaScript vectorFromArray dictionary 0.017 s -0.188
2023-01-19 13:02 JavaScript Iterate Vector int32Array 0.002 s 0.188
2023-01-19 13:02 JavaScript Spread Vector float64Array 0.008 s 0.944
2023-01-19 13:02 JavaScript toArray Vector numbers
2023-01-19 13:02 JavaScript get Vector uint64Array 0.003 s 1.542
2023-01-19 13:02 JavaScript Iterate Vector float32Array 0.002 s 0.764
2023-01-19 13:02 JavaScript Iterate Vector numbers 0.002 s 0.718
2023-01-19 13:02 JavaScript Iterate Vector booleans 0.004 s -0.601
2023-01-19 13:02 JavaScript Spread Vector string 0.146 s -0.174
2023-01-19 13:02 JavaScript toArray Vector booleans 0.010 s 0.365
2023-01-19 13:02 JavaScript Iterate Vector dictionary 0.004 s 0.492
2023-01-19 13:02 JavaScript Spread Vector uint16Array 0.006 s 0.486
2023-01-19 13:02 JavaScript Spread Vector uint64Array 0.012 s 0.923
2023-01-19 13:02 JavaScript Spread Vector int16Array 0.006 s 0.166
2023-01-19 13:02 JavaScript Spread Vector uint32Array 0.007 s 0.212
2023-01-19 13:02 JavaScript toArray Vector uint64Array
2023-01-19 13:02 JavaScript toArray Vector float32Array
2023-01-19 13:02 JavaScript Spread Vector int8Array 0.006 s 0.588
2023-01-19 13:02 JavaScript toArray Vector int64Array
2023-01-19 13:02 JavaScript get Vector int8Array 0.003 s 1.310
2023-01-19 13:02 JavaScript get Vector int32Array 0.003 s 0.889
2023-01-19 13:02 JavaScript Spread Vector int32Array 0.006 s 0.670
2023-01-19 13:02 JavaScript toArray Vector uint16Array
2023-01-19 13:02 JavaScript toArray Vector uint32Array
2023-01-19 13:02 JavaScript toArray Vector int16Array
2023-01-19 13:02 JavaScript get Vector float32Array 0.002 s -0.197
2023-01-19 13:02 JavaScript toArray Vector string 0.146 s -0.400
2023-01-19 13:02 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.405
2023-01-19 13:02 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -5.073
2023-01-19 13:02 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s -3.303
2023-01-19 13:03 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 1.046
2023-01-19 13:03 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-19 13:02 JavaScript get Vector uint16Array 0.003 s 1.104
2023-01-19 13:02 JavaScript get Vector uint32Array 0.003 s 0.961
2023-01-19 13:02 JavaScript get Vector string 0.125 s -0.479
2023-01-19 13:02 JavaScript Parse write recordBatches, tracks 0.002 s -3.952
2023-01-19 13:03 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.191 s -1.173
2023-01-19 13:03 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.187 s 0.410
2023-01-19 13:02 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.525
2023-01-19 13:03 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s 1.297
2023-01-19 13:03 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.228
2023-01-19 13:03 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-19 13:03 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-19 13:02 JavaScript get Vector int16Array 0.003 s 0.956
2023-01-19 13:03 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.813
2023-01-19 13:02 JavaScript get Vector int64Array 0.003 s 1.345
2023-01-19 13:02 JavaScript get Vector booleans 0.002 s -2.138
2023-01-19 13:02 JavaScript get Vector dictionary 0.002 s 1.778
2023-01-19 13:02 JavaScript Parse read recordBatches, tracks 0.000 s -4.774
2023-01-19 13:02 JavaScript get Vector float64Array 0.002 s 0.685
2023-01-19 13:02 JavaScript get Vector numbers 0.002 s 0.552
2023-01-19 13:02 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.562
2023-01-19 13:03 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -1.762
2023-01-19 13:02 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.447
2023-01-19 13:02 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s -3.245
2023-01-19 13:03 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-19 13:03 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.806
2023-01-19 13:03 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.839
2023-01-19 13:02 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.227
2023-01-19 13:03 JavaScript Table tracks, 1,000,000 0.050 s -0.424
2023-01-19 13:03 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.385
2023-01-19 13:03 JavaScript Table tracks, 1,000,000 0.094 s 0.929
2023-01-19 13:03 JavaScript Table 1,000,000, tracks 0.305 s -1.141
2023-01-19 13:03 JavaScript Table tracks, 1,000,000 0.292 s -1.132
2023-01-19 13:03 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.366