Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-15 23:52 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.436 s 0.340
2023-01-15 23:55 Python dataframe-to-table type_nested 2.945 s 1.171
2023-01-15 23:55 Python dataset-filter nyctaxi_2010-01 1.029 s -0.258
2023-01-16 00:16 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.261 s -2.576
2023-01-16 00:16 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.307 s -2.440
2023-01-15 23:55 Python dataframe-to-table chi_traffic_2020_Q1 21.020 s 0.564
2023-01-15 23:55 Python dataframe-to-table type_floats 0.010 s 0.146
2023-01-16 00:15 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.327 s -0.056
2023-01-16 00:15 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.888 s -4.328
2023-01-15 23:50 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.782 s 0.191
2023-01-15 23:51 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.069 s -1.087
2023-01-16 00:04 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 83.699 s -0.086
2023-01-16 00:21 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.150 s -0.187
2023-01-15 23:50 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.267 s 0.110
2023-01-15 23:51 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.132 s -1.385
2023-01-15 23:52 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.109 s 0.320
2023-01-15 23:52 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.556 s 0.964
2023-01-15 23:53 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.428 s 1.099
2023-01-15 23:55 Python dataframe-to-table type_strings 0.428 s -0.229
2023-01-15 23:55 Python dataframe-to-table type_dict 0.011 s 0.969
2023-01-15 23:55 Python dataframe-to-table type_integers 0.010 s 0.222
2023-01-15 23:59 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 81.992 s -0.122
2023-01-16 00:15 Python dataset-read async=True, nyctaxi_multi_ipc_s3 220.086 s 0.440
2023-01-16 00:15 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.905 s -4.523
2023-01-16 00:15 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.943 s -3.894
2023-01-16 00:16 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 3.760 s -4.719
2023-01-16 00:16 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.230 s -3.514
2023-01-16 00:17 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.550
2023-01-16 00:44 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.501 s 0.140
2023-01-16 00:45 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.212 s 0.402
2023-01-16 00:52 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.404 s -1.025
2023-01-16 00:16 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 3.741 s -4.188
2023-01-16 00:16 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 3.779 s -4.314
2023-01-16 00:17 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.933 s -1.837
2023-01-16 00:21 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.301 s -1.762
2023-01-16 00:30 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.522
2023-01-16 00:46 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.963 s 0.267
2023-01-16 00:46 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.933 s 0.342
2023-01-16 00:16 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.221 s -3.462
2023-01-16 00:30 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.224 s 0.908
2023-01-16 00:35 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.888 s -1.732
2023-01-16 00:35 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.404 s 1.821
2023-01-16 00:44 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.620 s 0.292
2023-01-16 00:46 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.944 s -0.038
2023-01-16 00:48 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.269 s -1.277
2023-01-16 00:17 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s -3.047
2023-01-16 00:30 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.047 s -1.717
2023-01-16 00:45 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.319 s 0.344
2023-01-16 00:45 Python file-read lz4, feather, table, fanniemae_2016Q4 0.816 s 0.268
2023-01-16 00:46 Python file-read lz4, feather, table, nyctaxi_2010-01 0.676 s 0.288
2023-01-16 00:17 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s 1.081
2023-01-16 00:17 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.760 s -0.170
2023-01-16 00:22 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.150 s 0.196
2023-01-16 00:30 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 75.981 s 1.357
2023-01-16 00:30 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.865 s 1.480
2023-01-16 00:31 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.684 s 1.583
2023-01-16 00:17 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 1.349
2023-01-16 00:30 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.225 s 0.523
2023-01-16 00:44 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.204 s 1.540
2023-01-16 00:47 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.749 s -1.622
2023-01-16 00:50 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.581 s -0.457
2023-01-16 00:18 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.526 s 1.366
2023-01-16 00:30 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.197
2023-01-16 00:44 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.633 s 0.365
2023-01-16 00:45 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.495 s 0.227
2023-01-16 00:30 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.287 s -1.614
2023-01-16 00:35 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.402 s 1.421
2023-01-16 00:48 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.935 s -1.770
2023-01-16 00:54 Python wide-dataframe use_legacy_dataset=true 0.377 s 0.235
2023-01-16 00:46 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.938 s 0.011
2023-01-16 00:46 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.589 s 0.317
2023-01-16 00:49 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.463 s -1.503
2023-01-16 00:53 Python file-write lz4, feather, table, nyctaxi_2010-01 1.818 s -0.187
2023-01-16 01:03 R dataframe-to-table type_floats, R 0.013 s 0.603
2023-01-16 01:04 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.323 s -0.103
2023-01-16 00:52 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.957 s -1.129
2023-01-16 00:45 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.617 s 0.366
2023-01-16 00:45 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.984 s -0.006
2023-01-16 00:46 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.330 s 0.340
2023-01-16 00:51 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.303 s -0.065
2023-01-16 00:51 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.986 s -0.508
2023-01-16 00:53 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.847 s -0.482
2023-01-16 00:51 Python file-write lz4, feather, table, fanniemae_2016Q4 1.877 s -0.130
2023-01-16 00:52 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.800 s -1.060
2023-01-16 00:53 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.238 s -0.439
2023-01-16 00:54 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.231 s -0.179
2023-01-16 00:53 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.317 s -1.302
2023-01-16 01:03 R dataframe-to-table type_integers, R 0.010 s 0.573
2023-01-16 01:03 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.322 s -0.156
2023-01-16 01:05 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.916 s -0.146
2023-01-16 01:06 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.581 s 0.307
2023-01-16 01:17 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.981 s -1.197
2023-01-16 00:54 Python wide-dataframe use_legacy_dataset=false 0.516 s 0.150
2023-01-16 01:04 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.580 s -0.273
2023-01-16 01:12 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.222 s -1.134
2023-01-16 01:02 R dataframe-to-table chi_traffic_2020_Q1, R 4.383 s -1.651
2023-01-16 01:04 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.574 s 0.255
2023-01-16 01:03 R dataframe-to-table type_nested, R 0.575 s -0.827
2023-01-16 01:05 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.569 s -0.171
2023-01-16 01:06 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.895 s 0.318
2023-01-16 01:14 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.492 s 0.345
2023-01-16 01:18 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.791 s -1.009
2023-01-16 01:06 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.816 s 0.324
2023-01-16 01:09 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.767 s -1.139
2023-01-16 01:14 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.030 s 0.265
2023-01-16 01:19 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.714 s -1.195
2023-01-16 01:05 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 1.666 s -4.987
2023-01-16 01:06 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.217 s 0.312
2023-01-16 01:02 R dataframe-to-table type_strings, R 0.535 s 0.022
2023-01-16 01:03 R dataframe-to-table type_dict, R 0.045 s 1.297
2023-01-16 01:04 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.313 s 0.262
2023-01-16 01:10 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.263 s -1.477
2023-01-16 01:16 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.441 s 1.208
2023-01-16 01:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.313 s 0.250
2023-01-16 01:04 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.577 s -0.255
2023-01-16 01:04 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.590 s 0.344
2023-01-16 01:05 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.914 s -0.093
2023-01-16 01:05 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.573 s -0.326
2023-01-16 01:07 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.854 s -1.512
2023-01-16 01:12 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.957 s 0.411
2023-01-16 01:20 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.753 s -1.145
2023-01-16 01:22 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.182 s -0.559
2023-01-16 01:21 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.307 s 1.127
2023-01-16 01:22 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.471 s -0.226
2023-01-16 01:24 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.539 s 1.185
2023-01-16 01:23 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.082 s -0.697
2023-01-16 01:24 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.611 s -1.202
2023-01-16 01:24 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.253 s -0.097
2023-01-16 01:24 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.241 s 0.219
2023-01-16 01:25 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.282 s 0.206
2023-01-16 01:24 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.199 s 0.289
2023-01-16 01:24 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.605 s -0.297
2023-01-16 01:25 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.274 s 0.169
2023-01-16 01:25 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.200 s 0.250
2023-01-16 01:25 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.588 s -0.051
2023-01-16 01:26 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -0.184
2023-01-16 01:26 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.083
2023-01-16 01:26 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.349 s 0.126
2023-01-16 01:25 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.004 s 0.062
2023-01-16 01:26 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.718 s 0.453
2023-01-16 01:26 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.290 s 0.082
2023-01-16 01:27 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.389 s -4.233
2023-01-16 01:27 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.515 s -3.389
2023-01-16 01:27 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.707 s -5.353
2023-01-16 01:28 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.302 s -4.539
2023-01-16 01:28 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.375 s -5.331
2023-01-16 01:28 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.192 s -6.404
2023-01-16 01:28 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.312 s -3.784
2023-01-16 01:29 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.320 s -1.399
2023-01-16 01:29 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.427 s -4.097
2023-01-16 01:29 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.586 s 0.128
2023-01-16 01:30 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.542 s -0.240
2023-01-16 01:29 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.897 s 0.108
2023-01-16 01:30 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.233 s 0.291
2023-01-16 01:30 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.319
2023-01-16 01:30 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.242 s 0.282
2023-01-16 01:30 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.200 s 0.289
2023-01-16 01:31 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.327 s 0.379
2023-01-16 01:30 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.269 s 0.390
2023-01-16 01:31 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.155
2023-01-16 01:31 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.913 s 0.205
2023-01-16 01:31 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.192 s 0.062
2023-01-16 01:32 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.267 s 0.159
2023-01-16 01:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.349 s 0.274
2023-01-16 01:32 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.637 s 0.186
2023-01-16 01:32 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.318 s 0.364
2023-01-16 01:33 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.634 s 0.018
2023-01-16 01:33 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.161 s 0.241
2023-01-16 01:33 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.769 s -1.019
2023-01-16 01:33 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.202 s 0.266
2023-01-16 01:33 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.161
2023-01-16 01:34 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.358
2023-01-16 01:34 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.179 s 0.282
2023-01-16 01:34 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.507 s 0.220
2023-01-16 01:34 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.354 s 0.171
2023-01-16 01:35 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.255 s 0.012
2023-01-16 01:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.329
2023-01-16 01:35 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.340 s 0.343
2023-01-16 01:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.293 s 0.305
2023-01-16 01:35 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.661 s 0.183
2023-01-16 01:35 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.351 s 0.257
2023-01-16 01:35 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.374 s 0.316
2023-01-16 01:36 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.335 s 0.227
2023-01-16 01:36 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.664 s -0.340
2023-01-16 01:36 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.786 s 0.096
2023-01-16 01:37 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.478 s -1.808
2023-01-16 01:37 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.573 s -3.649
2023-01-16 01:37 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.395 s -1.979
2023-01-16 01:38 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.427 s -2.430
2023-01-16 01:38 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.876 s -3.844
2023-01-16 01:39 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.655 s -2.663
2023-01-16 01:40 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.328 s -2.093
2023-01-16 01:39 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 4.295 s -3.743
2023-01-16 01:40 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.454 s -3.039
2023-01-16 01:40 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.351 s -2.420
2023-01-16 01:41 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.441 s 0.223
2023-01-16 01:40 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.492 s -2.877
2023-01-16 01:41 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.772 s 0.211
2023-01-16 01:42 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.122 s -0.029
2023-01-16 01:41 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.966 s -0.467
2023-01-16 01:42 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.257 s 0.108
2023-01-16 01:42 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.336 s 0.251
2023-01-16 01:42 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.299 s 0.294
2023-01-16 01:43 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.653 s 0.099
2023-01-16 01:42 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.260 s 0.206
2023-01-16 01:43 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.324 s -0.003
2023-01-16 01:43 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.881 s -0.254
2023-01-16 01:44 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.759 s -0.255
2023-01-16 01:44 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.232 s 0.149
2023-01-16 01:44 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.235
2023-01-16 01:44 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.335 s -0.311
2023-01-16 01:44 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.210 s 0.189
2023-01-16 01:44 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.542 s -0.062
2023-01-16 01:44 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.303 s 0.261
2023-01-16 01:45 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.211 s -0.023
2023-01-16 01:45 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.868 s 0.029
2023-01-16 01:45 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.301 s -1.181
2023-01-16 01:45 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.257 s 0.056
2023-01-16 01:45 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.304 s -0.202
2023-01-16 01:46 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.367 s -0.002
2023-01-16 01:46 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.496 s -1.529
2023-01-16 01:46 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.924 s -0.614
2023-01-16 01:46 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.705 s -3.186
2023-01-16 01:47 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.670 s -1.133
2023-01-16 01:47 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.240 s -0.025
2023-01-16 01:47 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.183 s 0.180
2023-01-16 01:47 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.334 s -0.165
2023-01-16 01:48 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.614 s -1.173
2023-01-16 01:48 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.866 s -0.331
2023-01-16 01:48 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.430 s -0.145
2023-01-16 01:48 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.444 s -2.712
2023-01-16 01:49 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.529 s -0.564
2023-01-16 01:49 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.265 s 0.302
2023-01-16 01:49 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.216 s 0.187
2023-01-16 01:49 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.190
2023-01-16 01:49 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.335 s 0.215
2023-01-16 01:50 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.942 s -0.017
2023-01-16 01:49 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.444 s -0.109
2023-01-16 01:50 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.604 s -1.343
2023-01-16 01:51 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 5.983 s -0.460
2023-01-16 01:51 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.210 s 0.272
2023-01-16 01:51 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.208 s 0.330
2023-01-16 01:51 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.335
2023-01-16 01:51 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.587 s 0.141
2023-01-16 01:51 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.284 s 0.278
2023-01-16 01:51 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.248
2023-01-16 01:52 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.582 s -0.143
2023-01-16 01:52 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.622 s -0.220
2023-01-16 01:53 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.222 s 0.215
2023-01-16 01:53 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.239 s 0.256
2023-01-16 01:53 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.285 s 0.267
2023-01-16 01:52 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.196 s 0.260
2023-01-16 01:53 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.529 s 0.156
2023-01-16 01:53 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.328 s 0.065
2023-01-16 01:53 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.899 s -0.672
2023-01-16 01:54 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.377 s -2.372
2023-01-16 01:54 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.287 s -2.601
2023-01-16 01:54 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.374 s -3.137
2023-01-16 01:55 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.301 s -3.297
2023-01-16 01:55 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.448 s -3.487
2023-01-16 01:55 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.333 s -3.157
2023-01-16 01:55 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 1.185 s -3.396
2023-01-16 01:56 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.718 s -2.875
2023-01-16 01:57 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 8.030 s -3.408
2023-01-16 01:57 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.237 s -2.554
2023-01-16 01:57 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.359 s -2.912
2023-01-16 01:57 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.252 s -1.861
2023-01-16 01:58 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.265 s 0.236
2023-01-16 01:58 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.537 s 0.132
2023-01-16 01:59 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.491 s -1.489
2023-01-16 01:58 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.412 s -0.347
2023-01-16 01:59 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s 0.108
2023-01-16 01:59 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.366 s -1.019
2023-01-16 01:59 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.328 s 0.224
2023-01-16 01:59 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.443 s -0.097
2023-01-16 01:59 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.444 s 0.110
2023-01-16 02:00 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.893 s -0.820
2023-01-16 02:00 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.340 s -0.480
2023-01-16 02:01 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.674 s -2.316
2023-01-16 02:01 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.258 s 0.074
2023-01-16 02:01 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.494 s -2.352
2023-01-16 02:01 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.320 s 0.156
2023-01-16 02:02 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.371 s 0.188
2023-01-16 02:02 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.288 s 0.093
2023-01-16 02:02 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.258 s 0.080
2023-01-16 02:02 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.970 s -0.006
2023-01-16 02:03 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.605 s -0.014
2023-01-16 02:03 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.193 s -0.664
2023-01-16 02:04 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.739 s -1.145
2023-01-16 02:03 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.452 s 0.010
2023-01-16 02:03 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.397 s -0.425
2023-01-16 02:04 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.803 s -0.297
2023-01-16 02:04 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.897 s -1.216
2023-01-16 02:04 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.178 s -1.658
2023-01-16 02:07 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.177 s -2.633
2023-01-16 02:08 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.294 s -2.913
2023-01-16 02:09 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.227 s 0.230
2023-01-16 02:09 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.155
2023-01-16 02:09 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.242 s 0.249
2023-01-16 02:09 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.203 s 0.268
2023-01-16 02:09 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.262 s 0.203
2023-01-16 02:09 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.460 s -0.083
2023-01-16 02:10 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.310 s 0.108
2023-01-16 02:10 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.318 s -0.041
2023-01-16 02:18 JavaScript Iterate Vector int64Array 0.004 s 0.057
2023-01-16 02:18 JavaScript Spread Vector int8Array 0.006 s 1.275
2023-01-16 02:18 JavaScript vectorFromArray numbers 0.016 s 0.634
2023-01-16 02:18 JavaScript vectorFromArray booleans 0.017 s 0.554
2023-01-16 02:18 JavaScript Iterate Vector uint32Array 0.002 s -0.427
2023-01-16 02:18 JavaScript Iterate Vector uint64Array 0.004 s 0.102
2023-01-16 02:18 JavaScript Spread Vector booleans 0.010 s 0.160
2023-01-16 02:18 JavaScript Spread Vector string 0.144 s 1.066
2023-01-16 02:19 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s -0.027
2023-01-16 02:18 JavaScript Spread Vector int32Array 0.006 s 1.017
2023-01-16 02:18 JavaScript Spread Vector numbers 0.008 s -1.531
2023-01-16 02:19 JavaScript toArray Vector dictionary 0.010 s -1.034
2023-01-16 02:19 JavaScript get Vector float64Array 0.002 s -0.107
2023-01-16 02:19 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.579
2023-01-16 02:18 JavaScript Iterate Vector string 0.125 s 0.612
2023-01-16 02:18 JavaScript Spread Vector uint16Array 0.006 s 0.578
2023-01-16 02:18 JavaScript Spread Vector uint64Array 0.012 s -0.198
2023-01-16 02:18 JavaScript toArray Vector int16Array
2023-01-16 02:19 JavaScript toArray Vector int64Array
2023-01-16 02:19 JavaScript toArray Vector float64Array
2023-01-16 02:18 JavaScript vectorFromArray dictionary 0.017 s -1.213
2023-01-16 02:18 JavaScript Iterate Vector uint8Array 0.002 s 1.350
2023-01-16 02:18 JavaScript Iterate Vector float32Array 0.002 s 0.004
2023-01-16 02:18 JavaScript Iterate Vector float64Array 0.002 s 0.725
2023-01-16 02:18 JavaScript Iterate Vector uint16Array 0.002 s 0.387
2023-01-16 02:18 JavaScript Spread Vector int16Array 0.007 s 0.026
2023-01-16 02:18 JavaScript toArray Vector int8Array
2023-01-16 02:18 JavaScript Iterate Vector int8Array 0.002 s 1.032
2023-01-16 02:18 JavaScript Iterate Vector int16Array 0.002 s 0.186
2023-01-16 02:18 JavaScript Iterate Vector int32Array 0.002 s 0.607
2023-01-16 02:18 JavaScript Iterate Vector numbers 0.002 s 0.707
2023-01-16 02:18 JavaScript Iterate Vector booleans 0.004 s 0.114
2023-01-16 02:18 JavaScript Iterate Vector dictionary 0.004 s 0.783
2023-01-16 02:18 JavaScript Spread Vector uint32Array 0.007 s -0.330
2023-01-16 02:19 JavaScript toArray Vector float32Array
2023-01-16 02:19 JavaScript get Vector uint16Array 0.003 s 0.078
2023-01-16 02:18 JavaScript Spread Vector uint8Array 0.007 s -0.088
2023-01-16 02:18 JavaScript Spread Vector dictionary 0.010 s -1.920
2023-01-16 02:19 JavaScript toArray Vector booleans 0.010 s 0.752
2023-01-16 02:19 JavaScript get Vector int64Array 0.003 s -0.056
2023-01-16 02:18 JavaScript Spread Vector int64Array 0.012 s -0.508
2023-01-16 02:18 JavaScript Spread Vector float64Array 0.008 s -1.084
2023-01-16 02:18 JavaScript toArray Vector uint32Array
2023-01-16 02:19 JavaScript toArray Vector int32Array
2023-01-16 02:18 JavaScript Spread Vector float32Array 0.008 s 0.103
2023-01-16 02:19 JavaScript get Vector uint32Array 0.003 s 0.082
2023-01-16 02:19 JavaScript get Vector int8Array 0.003 s 0.140
2023-01-16 02:19 JavaScript get Vector float32Array 0.002 s 0.174
2023-01-16 02:19 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.163
2023-01-16 02:18 JavaScript toArray Vector uint8Array
2023-01-16 02:19 JavaScript get Vector uint64Array 0.003 s -0.133
2023-01-16 02:19 JavaScript get Vector int16Array 0.003 s 0.086
2023-01-16 02:18 JavaScript toArray Vector uint16Array
2023-01-16 02:19 JavaScript get Vector int32Array 0.003 s 0.142
2023-01-16 02:19 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-16 02:19 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.192 s -1.558
2023-01-16 02:19 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.190 s -0.602
2023-01-16 02:19 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.884
2023-01-16 02:18 JavaScript toArray Vector uint64Array
2023-01-16 02:19 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.674
2023-01-16 02:19 JavaScript Table 1,000,000, tracks 0.317 s -1.730
2023-01-16 02:19 JavaScript toArray Vector numbers
2023-01-16 02:19 JavaScript toArray Vector string 0.145 s 0.308
2023-01-16 02:19 JavaScript get Vector uint8Array 0.003 s 0.119
2023-01-16 02:19 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.575
2023-01-16 02:19 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.974
2023-01-16 02:19 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.915
2023-01-16 02:19 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s 0.529
2023-01-16 02:19 JavaScript get Vector numbers 0.002 s 0.232
2023-01-16 02:19 JavaScript get Vector booleans 0.002 s 0.728
2023-01-16 02:19 JavaScript get Vector dictionary 0.002 s -0.772
2023-01-16 02:19 JavaScript get Vector string 0.123 s 1.575
2023-01-16 02:19 JavaScript Parse read recordBatches, tracks 0.000 s 0.390
2023-01-16 02:19 JavaScript Parse write recordBatches, tracks 0.002 s 0.942
2023-01-16 02:19 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s -0.041
2023-01-16 02:19 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s 1.293
2023-01-16 02:19 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.684
2023-01-16 02:19 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.079
2023-01-16 02:19 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-16 02:19 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-16 02:19 JavaScript Table tracks, 1,000,000 0.050 s 0.693
2023-01-16 02:19 JavaScript Table tracks, 1,000,000 0.289 s -0.917
2023-01-16 02:19 JavaScript Table tracks, 1,000,000 0.094 s 0.860
2023-01-16 02:19 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-16 02:19 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -1.147
2023-01-16 02:19 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.697
2023-01-16 02:19 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.380
2023-01-16 02:19 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s 0.387