Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-17 02:10 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.082 s -1.145
2023-01-17 02:09 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.770 s 1.010
2023-01-17 02:10 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.243 s 0.267
2023-01-17 02:12 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.116 s 0.256
2023-01-17 02:11 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.002 s -0.983
2023-01-17 02:11 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.434 s 0.577
2023-01-17 02:12 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.435 s 1.299
2023-01-17 02:13 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.396 s 1.233
2023-01-17 02:14 Python dataframe-to-table chi_traffic_2020_Q1 21.051 s 0.240
2023-01-17 02:15 Python dataframe-to-table type_dict 0.011 s 0.949
2023-01-17 02:15 Python dataframe-to-table type_strings 0.425 s 0.828
2023-01-17 02:15 Python dataframe-to-table type_integers 0.010 s 1.325
2023-01-17 02:15 Python dataframe-to-table type_floats 0.010 s 0.264
2023-01-17 02:15 Python dataframe-to-table type_nested 2.971 s -0.115
2023-01-17 02:15 Python dataset-filter nyctaxi_2010-01 1.162 s -2.952
2023-01-17 02:20 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 91.759 s -1.178
2023-01-17 02:25 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 93.934 s -5.667
2023-01-17 02:37 Python dataset-read async=True, nyctaxi_multi_ipc_s3 258.306 s -5.163
2023-01-17 02:38 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.309 s 0.207
2023-01-17 02:38 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.562 s -1.800
2023-01-17 02:38 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.207 s 0.052
2023-01-17 02:38 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.646 s 0.306
2023-01-17 02:38 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.176 s -0.551
2023-01-17 02:38 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.039 s 0.295
2023-01-17 02:38 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.203 s 0.282
2023-01-17 02:38 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.037 s 0.281
2023-01-17 02:39 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.757 s 1.101
2023-01-17 02:39 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.306 s -1.349
2023-01-17 02:38 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.203 s -0.010
2023-01-17 02:39 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.139 s -0.123
2023-01-17 02:39 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.201
2023-01-17 02:39 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s -0.284
2023-01-17 02:39 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.446
2023-01-17 02:39 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.933 s -1.471
2023-01-17 02:39 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.200 s -2.064
2023-01-17 02:40 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.526 s 1.172
2023-01-17 02:43 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.298 s -1.369
2023-01-17 02:44 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.155 s -1.568
2023-01-17 02:43 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.147 s 0.955
2023-01-17 02:51 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.002 s 1.070
2023-01-17 02:51 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.209
2023-01-17 02:51 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.287 s -1.323
2023-01-17 02:52 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.046 s -1.396
2023-01-17 02:51 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.971
2023-01-17 02:52 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.866 s 0.956
2023-01-17 02:52 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.226 s -1.276
2023-01-17 02:52 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.562
2023-01-17 02:53 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.685 s 1.292
2023-01-17 02:56 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.873 s -1.371
2023-01-17 02:57 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.405 s 0.781
2023-01-17 02:57 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.406 s 1.153
2023-01-17 03:06 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.243 s 1.115
2023-01-17 03:07 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.214 s 0.238
2023-01-17 03:07 Python file-read lz4, feather, table, nyctaxi_2010-01 0.664 s 0.437
2023-01-17 03:06 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.619 s 0.498
2023-01-17 03:07 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.622 s 0.336
2023-01-17 03:07 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.928 s 0.380
2023-01-17 03:06 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.488 s 0.497
2023-01-17 03:06 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.644 s -0.042
2023-01-17 03:06 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.478 s 0.834
2023-01-17 03:07 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.992 s -0.078
2023-01-17 03:07 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.910 s 0.386
2023-01-17 03:06 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.321 s 0.340
2023-01-17 03:07 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.975 s 0.127
2023-01-17 03:12 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.197 s 0.011
2023-01-17 03:13 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 6.011 s -1.409
2023-01-17 03:15 Python file-write lz4, feather, table, nyctaxi_2010-01 1.823 s -0.280
2023-01-17 03:07 Python file-read lz4, feather, table, fanniemae_2016Q4 0.822 s 0.122
2023-01-17 03:08 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.664 s -1.026
2023-01-17 03:11 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.489 s -1.559
2023-01-17 03:13 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.951 s -0.347
2023-01-17 03:14 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.461 s -1.366
2023-01-17 03:15 Python wide-dataframe use_legacy_dataset=false 0.513 s 0.385
2023-01-17 03:11 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.231 s 0.070
2023-01-17 03:07 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.936 s 0.083
2023-01-17 03:07 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.588 s 0.343
2023-01-17 03:08 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.348 s 0.188
2023-01-17 03:12 Python file-write lz4, feather, table, fanniemae_2016Q4 1.869 s -0.117
2023-01-17 03:14 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.359 s -1.520
2023-01-17 03:15 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.768 s -0.176
2023-01-17 03:09 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.318 s -1.511
2023-01-17 03:10 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.946 s -1.585
2023-01-17 03:14 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.897 s -1.732
2023-01-17 03:15 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.143 s -0.092
2023-01-17 03:15 Python wide-dataframe use_legacy_dataset=true 0.377 s 0.269
2023-01-17 03:15 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.236 s -0.271
2023-01-17 03:38 R dataframe-to-table type_integers, R 0.010 s 0.563
2023-01-17 03:40 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.576 s -0.212
2023-01-17 03:40 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.570 s 0.269
2023-01-17 03:42 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.894 s 0.323
2023-01-17 03:41 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.912 s -0.055
2023-01-17 03:41 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.815 s 0.326
2023-01-17 03:38 R dataframe-to-table type_dict, R 0.047 s 0.893
2023-01-17 03:38 R dataframe-to-table type_strings, R 0.536 s -0.442
2023-01-17 03:39 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.320 s -0.057
2023-01-17 03:40 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.591 s 0.334
2023-01-17 03:39 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.321 s -0.116
2023-01-17 03:40 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.315 s 0.253
2023-01-17 03:41 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.218 s 0.300
2023-01-17 03:38 R dataframe-to-table chi_traffic_2020_Q1, R 4.386 s -1.378
2023-01-17 03:39 R dataframe-to-table type_nested, R 0.573 s -0.057
2023-01-17 03:41 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.590 s 0.274
2023-01-17 03:38 R dataframe-to-table type_floats, R 0.013 s 0.459
2023-01-17 03:39 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.576 s -0.233
2023-01-17 03:40 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.847 s 0.292
2023-01-17 03:41 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.913 s -0.065
2023-01-17 03:40 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.569 s -0.160
2023-01-17 03:41 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.572 s -0.308
2023-01-17 03:43 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.918 s -1.616
2023-01-17 03:47 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.298 s -1.361
2023-01-17 03:48 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.956 s 0.616
2023-01-17 03:44 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.904 s -1.687
2023-01-17 03:53 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.891 s -1.864
2023-01-17 03:56 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.313 s -0.832
2023-01-17 03:52 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 5.079 s -2.075
2023-01-17 03:51 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.441 s 1.159
2023-01-17 03:56 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.863 s -2.180
2023-01-17 03:57 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.170 s -0.145
2023-01-17 04:02 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.671 s -1.440
2023-01-17 04:03 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.269 s 0.216
2023-01-17 04:03 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.303 s 0.243
2023-01-17 03:45 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.338 s -1.650
2023-01-17 03:54 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.818 s -2.124
2023-01-17 03:59 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.604 s -0.943
2023-01-17 03:59 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.256 s -0.455
2023-01-17 04:00 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.200 s 0.275
2023-01-17 04:02 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.349 s 0.141
2023-01-17 04:02 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.334 s 0.320
2023-01-17 03:50 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.492 s 0.128
2023-01-17 04:01 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.001 s 0.397
2023-01-17 04:03 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.183
2023-01-17 04:06 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.351 s 0.236
2023-01-17 03:49 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.009 s 0.717
2023-01-17 04:00 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.239 s 0.267
2023-01-17 04:01 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.280 s 0.030
2023-01-17 04:04 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.349
2023-01-17 04:00 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.592 s -0.229
2023-01-17 04:05 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.273 s 0.075
2023-01-17 04:06 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.200 s -0.103
2023-01-17 04:07 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.637 s 0.178
2023-01-17 04:09 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.292 s 0.344
2023-01-17 04:10 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.351 s 0.277
2023-01-17 04:12 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.785 s -0.164
2023-01-17 03:59 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.076 s -0.317
2023-01-17 04:03 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.232 s 0.234
2023-01-17 04:04 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.232 s 0.323
2023-01-17 04:06 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.313 s 0.245
2023-01-17 04:07 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.634 s 0.062
2023-01-17 04:09 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.373 s 0.320
2023-01-17 04:10 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.789 s -0.002
2023-01-17 04:11 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.340 s 0.254
2023-01-17 04:15 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.336 s 0.241
2023-01-17 04:15 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.651 s 0.199
2023-01-17 03:58 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.472 s -0.651
2023-01-17 03:59 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.555 s 0.373
2023-01-17 04:00 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.199 s 0.282
2023-01-17 04:00 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.283 s 0.174
2023-01-17 04:00 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.272 s 0.326
2023-01-17 04:05 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.201 s 0.292
2023-01-17 04:00 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.620 s -1.343
2023-01-17 04:02 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.112
2023-01-17 04:02 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.077 s -1.003
2023-01-17 04:06 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.324 s -0.012
2023-01-17 04:15 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.320 s 0.331
2023-01-17 04:16 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.261 s 0.231
2023-01-17 04:19 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.609 s -0.826
2023-01-17 04:19 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.184 s 0.138
2023-01-17 04:01 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 4.059 s -1.932
2023-01-17 04:03 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.589 s 0.064
2023-01-17 04:04 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.596 s -0.580
2023-01-17 04:06 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.265 s 0.237
2023-01-17 04:09 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.338 s 0.389
2023-01-17 04:10 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.663 s 0.164
2023-01-17 04:12 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.615 s 0.133
2023-01-17 04:14 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.972 s -0.763
2023-01-17 04:14 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.177 s -0.375
2023-01-17 04:02 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.289 s 0.213
2023-01-17 04:03 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.303 s 0.028
2023-01-17 04:05 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.243 s 0.268
2023-01-17 04:05 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.333 s 0.239
2023-01-17 04:08 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.178 s 0.290
2023-01-17 04:08 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.507 s 0.235
2023-01-17 04:09 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.350
2023-01-17 04:11 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.369 s 0.252
2023-01-17 04:13 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.770 s 0.244
2023-01-17 04:15 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.259 s 0.263
2023-01-17 04:16 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.211 s 0.153
2023-01-17 04:20 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.613 s -0.938
2023-01-17 04:02 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.433 s 0.151
2023-01-17 04:04 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.903 s -0.204
2023-01-17 04:05 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.923 s -0.244
2023-01-17 04:06 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.198
2023-01-17 04:08 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.203 s 0.202
2023-01-17 04:08 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.234 s 0.307
2023-01-17 04:13 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.295 s 0.336
2023-01-17 04:14 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.299 s 0.264
2023-01-17 04:17 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.877 s -0.674
2023-01-17 04:07 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.806 s -1.331
2023-01-17 04:11 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.428 s 0.248
2023-01-17 04:16 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.231 s 0.188
2023-01-17 04:18 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.305 s -0.227
2023-01-17 04:20 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.334 s -0.112
2023-01-17 04:21 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.444 s -0.105
2023-01-17 04:24 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.610 s -0.322
2023-01-17 04:24 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.238 s 0.290
2023-01-17 04:08 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.161 s 0.242
2023-01-17 04:08 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.160 s 0.248
2023-01-17 04:09 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.357 s 0.064
2023-01-17 04:12 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.719 s 0.154
2023-01-17 04:12 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.271 s 0.336
2023-01-17 04:13 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.443 s 0.089
2023-01-17 04:16 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.335 s -0.300
2023-01-17 04:17 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.280 s -0.840
2023-01-17 04:19 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.684 s -1.891
2023-01-17 04:09 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.242 s 0.224
2023-01-17 04:13 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.373 s 0.265
2023-01-17 04:16 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.714 s 0.195
2023-01-17 04:23 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.209 s 0.299
2023-01-17 04:23 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.285 s 0.269
2023-01-17 04:23 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.590 s 0.099
2023-01-17 04:28 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.241 s 0.306
2023-01-17 04:30 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.894 s -0.851
2023-01-17 04:11 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.669 s -0.319
2023-01-17 04:11 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.332 s 0.343
2023-01-17 04:11 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.395 s 0.310
2023-01-17 04:13 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.324 s 0.344
2023-01-17 04:15 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.879 s -0.253
2023-01-17 04:16 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.304 s 0.226
2023-01-17 04:18 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.935 s -0.737
2023-01-17 04:19 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.240 s 0.023
2023-01-17 04:23 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.289
2023-01-17 04:23 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.239
2023-01-17 04:32 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.256 s 0.205
2023-01-17 04:14 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.255 s 0.250
2023-01-17 04:17 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.257 s 0.064
2023-01-17 04:18 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.367 s 0.031
2023-01-17 04:20 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.429 s -0.053
2023-01-17 04:21 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.267 s 0.261
2023-01-17 04:22 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.936 s 0.083
2023-01-17 04:23 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 6.036 s -0.557
2023-01-17 04:17 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.544 s -0.122
2023-01-17 04:17 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s 0.162
2023-01-17 04:21 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.550 s -0.625
2023-01-17 04:26 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.216 s 0.307
2023-01-17 04:26 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.267 s 0.289
2023-01-17 04:29 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.488 s -1.363
2023-01-17 04:29 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.343 s -0.657
2023-01-17 04:18 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.490 s -0.816
2023-01-17 04:21 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.216 s 0.195
2023-01-17 04:21 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.214
2023-01-17 04:24 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.626 s -0.291
2023-01-17 04:28 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.265 s 0.244
2023-01-17 04:28 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.407 s -0.036
2023-01-17 04:29 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.272 s 0.219
2023-01-17 04:32 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.287 s 0.147
2023-01-17 04:20 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.865 s -0.219
2023-01-17 04:21 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.335 s 0.228
2023-01-17 04:22 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.514 s 0.598
2023-01-17 04:25 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.284 s 0.288
2023-01-17 04:27 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 7.149 s -0.772
2023-01-17 04:32 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.371 s 0.196
2023-01-17 04:20 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.447 s -1.945
2023-01-17 04:23 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.339
2023-01-17 04:25 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.105 s -0.045
2023-01-17 04:26 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.321 s 0.312
2023-01-17 04:29 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.327 s 0.245
2023-01-17 04:31 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.457 s -1.540
2023-01-17 04:33 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.605 s 0.002
2023-01-17 04:24 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.195 s 0.331
2023-01-17 04:25 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.528 s 0.194
2023-01-17 04:26 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.964 s 0.177
2023-01-17 04:32 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.257 s 0.159
2023-01-17 04:25 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.221 s 0.293
2023-01-17 04:25 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.325 s 0.260
2023-01-17 04:26 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.220 s 0.249
2023-01-17 04:27 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.665 s 0.228
2023-01-17 04:39 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.183 s -1.901
2023-01-17 04:25 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.884 s 0.213
2023-01-17 04:33 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.396 s -0.156
2023-01-17 04:34 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.737 s -0.800
2023-01-17 04:39 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.458 s 0.000
2023-01-17 04:40 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.325 s -0.078
2023-01-17 04:26 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.259 s 0.249
2023-01-17 04:27 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.193 s 0.350
2023-01-17 04:28 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.208 s 0.323
2023-01-17 04:28 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.547 s -0.128
2023-01-17 04:30 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.447 s -0.063
2023-01-17 04:30 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.331 s -0.129
2023-01-17 04:30 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.442 s -0.018
2023-01-17 04:31 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.677 s -1.881
2023-01-17 04:32 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.320 s 0.163
2023-01-17 04:32 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.965 s 0.099
2023-01-17 04:33 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.156 s -0.435
2023-01-17 04:33 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.453 s -0.062
2023-01-17 04:39 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.243 s 0.207
2023-01-17 04:34 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.799 s -0.158
2023-01-17 04:39 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.226 s 0.284
2023-01-17 04:34 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.911 s -1.483
2023-01-17 04:34 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.219 s -2.448
2023-01-17 04:37 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.191 s -2.015
2023-01-17 04:39 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.113
2023-01-17 04:39 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.203 s 0.263
2023-01-17 04:39 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.260 s 0.255
2023-01-17 04:40 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.309 s 0.162
2023-01-17 04:48 JavaScript vectorFromArray numbers 0.016 s -0.441
2023-01-17 04:48 JavaScript vectorFromArray dictionary 0.017 s 0.232
2023-01-17 04:48 JavaScript Iterate Vector uint64Array 0.004 s 0.131
2023-01-17 04:48 JavaScript Iterate Vector int16Array 0.002 s 0.044
2023-01-17 04:48 JavaScript Spread Vector uint16Array 0.006 s -0.008
2023-01-17 04:48 JavaScript Spread Vector int64Array 0.012 s 0.148
2023-01-17 04:48 JavaScript get Vector uint8Array 0.003 s 0.226
2023-01-17 04:49 JavaScript Table tracks, 1,000,000 0.050 s 0.211
2023-01-17 04:48 JavaScript Iterate Vector uint8Array 0.002 s -0.861
2023-01-17 04:48 JavaScript Iterate Vector int8Array 0.002 s -0.753
2023-01-17 04:48 JavaScript Iterate Vector int32Array 0.002 s 0.046
2023-01-17 04:48 JavaScript Iterate Vector uint32Array 0.002 s 0.446
2023-01-17 04:48 JavaScript Spread Vector numbers 0.008 s -0.015
2023-01-17 04:48 JavaScript Spread Vector dictionary 0.010 s 0.358
2023-01-17 04:48 JavaScript vectorFromArray booleans 0.017 s 0.478
2023-01-17 04:48 JavaScript Iterate Vector numbers 0.002 s -0.458
2023-01-17 04:48 JavaScript Iterate Vector dictionary 0.004 s 1.199
2023-01-17 04:48 JavaScript Spread Vector string 0.146 s -0.340
2023-01-17 04:48 JavaScript Spread Vector float32Array 0.008 s 0.648
2023-01-17 04:48 JavaScript toArray Vector int8Array
2023-01-17 04:48 JavaScript toArray Vector float32Array
2023-01-17 04:48 JavaScript get Vector int8Array 0.003 s 0.191
2023-01-17 04:48 JavaScript get Vector int32Array 0.003 s 0.229
2023-01-17 04:48 JavaScript Iterate Vector float32Array 0.002 s 0.233
2023-01-17 04:48 JavaScript Spread Vector int8Array 0.006 s 0.511
2023-01-17 04:48 JavaScript Spread Vector int32Array 0.006 s 0.488
2023-01-17 04:49 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.306
2023-01-17 04:49 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.696
2023-01-17 04:48 JavaScript Iterate Vector uint16Array 0.002 s 0.585
2023-01-17 04:48 JavaScript Iterate Vector int64Array 0.004 s 0.158
2023-01-17 04:48 JavaScript Spread Vector float64Array 0.008 s -0.044
2023-01-17 04:48 JavaScript toArray Vector numbers
2023-01-17 04:48 JavaScript get Vector numbers 0.002 s 0.867
2023-01-17 04:48 JavaScript Iterate Vector float64Array 0.002 s -0.376
2023-01-17 04:48 JavaScript Iterate Vector booleans 0.004 s -2.342
2023-01-17 04:48 JavaScript Iterate Vector string 0.125 s 0.835
2023-01-17 04:48 JavaScript Spread Vector uint64Array 0.012 s 0.299
2023-01-17 04:48 JavaScript Spread Vector int16Array 0.006 s 0.551
2023-01-17 04:48 JavaScript Spread Vector booleans 0.010 s -0.084
2023-01-17 04:48 JavaScript toArray Vector booleans 0.010 s -0.410
2023-01-17 04:48 JavaScript get Vector float64Array 0.002 s -1.449
2023-01-17 04:48 JavaScript get Vector booleans 0.002 s -3.249
2023-01-17 04:49 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.247
2023-01-17 04:48 JavaScript Spread Vector uint8Array 0.006 s 0.501
2023-01-17 04:48 JavaScript Spread Vector uint32Array 0.007 s 0.056
2023-01-17 04:48 JavaScript get Vector int16Array 0.003 s 0.192
2023-01-17 04:48 JavaScript Parse write recordBatches, tracks 0.002 s 0.218
2023-01-17 04:49 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-17 04:48 JavaScript toArray Vector uint8Array
2023-01-17 04:48 JavaScript toArray Vector uint32Array
2023-01-17 04:48 JavaScript toArray Vector int32Array
2023-01-17 04:48 JavaScript get Vector uint64Array 0.003 s 0.217
2023-01-17 04:49 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.189 s -0.460
2023-01-17 04:49 JavaScript Table tracks, 1,000,000 0.094 s 1.062
2023-01-17 04:48 JavaScript toArray Vector uint16Array
2023-01-17 04:48 JavaScript toArray Vector uint64Array
2023-01-17 04:48 JavaScript toArray Vector int16Array
2023-01-17 04:48 JavaScript toArray Vector dictionary 0.010 s -0.287
2023-01-17 04:48 JavaScript get Vector uint32Array 0.003 s 0.189
2023-01-17 04:49 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.101
2023-01-17 04:48 JavaScript toArray Vector float64Array
2023-01-17 04:48 JavaScript toArray Vector string 0.145 s 0.102
2023-01-17 04:48 JavaScript get Vector uint16Array 0.003 s 0.179
2023-01-17 04:48 JavaScript get Vector int64Array 0.003 s 0.165
2023-01-17 04:48 JavaScript get Vector string 0.125 s -0.157
2023-01-17 04:49 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.376
2023-01-17 04:48 JavaScript toArray Vector int64Array
2023-01-17 04:49 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.427
2023-01-17 04:49 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.210
2023-01-17 04:49 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.806
2023-01-17 04:49 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.497
2023-01-17 04:49 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-17 04:49 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.193
2023-01-17 04:48 JavaScript get Vector float32Array 0.002 s 0.600
2023-01-17 04:48 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s -0.007
2023-01-17 04:49 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.045
2023-01-17 04:49 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -0.246
2023-01-17 04:48 JavaScript get Vector dictionary 0.002 s -1.592
2023-01-17 04:48 JavaScript Parse read recordBatches, tracks 0.000 s 1.228
2023-01-17 04:49 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.322
2023-01-17 04:49 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.087
2023-01-17 04:49 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-17 04:49 JavaScript Table tracks, 1,000,000 0.249 s 1.131
2023-01-17 04:49 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-17 04:49 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.187 s 0.159
2023-01-17 04:49 JavaScript Table 1,000,000, tracks 0.247 s 1.241
2023-01-17 04:49 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.523
2023-01-17 04:49 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.289