Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-16 14:13:16 UTC Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.771 s 1.014
2023-01-16 14:18:17 UTC Python dataframe-to-table chi_traffic_2020_Q1 21.066 s 0.237
2023-01-16 14:18:33 UTC Python dataframe-to-table type_floats 0.010 s 0.027
2023-01-16 14:14:53 UTC Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.024 s -1.050
2023-01-16 14:14:09 UTC Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.156 s -1.392
2023-01-16 14:16:31 UTC Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.433 s 1.147
2023-01-16 14:18:54 UTC Python dataset-filter nyctaxi_2010-01 1.024 s -0.166
2023-01-16 14:13:24 UTC Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.225 s 0.387
2023-01-16 14:15:20 UTC Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.439 s -0.071
2023-01-16 14:18:30 UTC Python dataframe-to-table type_dict 0.011 s 2.135
2023-01-16 14:18:48 UTC Python dataframe-to-table type_nested 2.955 s 0.783
2023-01-16 14:18:32 UTC Python dataframe-to-table type_integers 0.010 s 0.631
2023-01-16 14:15:25 UTC Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.113 s 0.277
2023-01-16 14:15:58 UTC Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.587 s 0.953
2023-01-16 14:18:29 UTC Python dataframe-to-table type_strings 0.430 s -0.859
2023-01-16 14:22:29 UTC Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 70.136 s 1.225
2023-01-16 14:26:43 UTC Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 83.208 s 0.462
2023-01-16 14:37:51 UTC Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.214 s 0.722
2023-01-16 14:37:44 UTC Python dataset-read async=True, nyctaxi_multi_ipc_s3 219.459 s 0.556
2023-01-16 14:37:57 UTC Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.199 s 0.098
2023-01-16 14:38:08 UTC Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.292 s 0.301
2023-01-16 14:38:17 UTC Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.060 s 0.245
2023-01-16 14:38:37 UTC Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.169 s -0.231
2023-01-16 14:38:03 UTC Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.212 s 0.223
2023-01-16 14:38:32 UTC Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.652 s 0.296
2023-01-16 14:38:25 UTC Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.043 s 0.267
2023-01-16 14:38:42 UTC Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.211 s -0.322
2023-01-16 14:38:48 UTC Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.133 s 0.088
2023-01-16 14:39:03 UTC Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.757 s 1.094
2023-01-16 14:38:54 UTC Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.079
2023-01-16 14:38:56 UTC Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s 1.182
2023-01-16 14:38:52 UTC Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.306 s -1.602
2023-01-16 14:39:22 UTC Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.932 s -1.759
2023-01-16 14:39:25 UTC Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s 1.454
2023-01-16 14:39:28 UTC Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.395
2023-01-16 14:40:15 UTC Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.528 s 1.164
2023-01-16 14:43:20 UTC Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.329 s -2.012
2023-01-16 14:43:56 UTC Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.151 s 0.021
2023-01-16 14:43:38 UTC Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.144 s 2.299
2023-01-16 14:51:41 UTC Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.288 s -1.688
2023-01-16 14:51:46 UTC Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.147
2023-01-16 14:51:44 UTC Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s -0.153
2023-01-16 14:52:18 UTC Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.225 s -0.118
2023-01-16 14:51:37 UTC Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.013 s 1.082
2023-01-16 14:51:53 UTC Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.865 s 1.536
2023-01-16 14:52:14 UTC Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.050 s -1.708
2023-01-16 14:52:22 UTC Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.497
2023-01-16 14:53:16 UTC Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.689 s 1.242
2023-01-16 14:56:27 UTC Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.909 s -1.666
2023-01-16 14:56:47 UTC Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.402 s 1.441
2023-01-16 14:57:08 UTC Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.405 s 1.645
2023-01-16 15:05:52 UTC Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.224 s 1.332
2023-01-16 15:06:09 UTC Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.615 s 0.353
2023-01-16 15:06:21 UTC Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.497 s 0.126
2023-01-16 15:06:15 UTC Python file-read snappy, parquet, table, fanniemae_2016Q4 1.487 s 0.546
2023-01-16 15:06:01 UTC Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.635 s 0.327
2023-01-16 15:06:50 UTC Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.653 s 0.268
2023-01-16 15:06:55 UTC Python file-read lz4, feather, table, fanniemae_2016Q4 0.835 s -0.158
2023-01-16 15:06:29 UTC Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.342 s 0.290
2023-01-16 15:07:11 UTC Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.220 s 0.181
2023-01-16 15:07:25 UTC Python file-read snappy, parquet, table, nyctaxi_2010-01 0.937 s 0.045
2023-01-16 15:07:44 UTC Python file-read lz4, feather, table, nyctaxi_2010-01 0.701 s 0.051
2023-01-16 15:07:29 UTC Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.925 s 0.213
2023-01-16 15:07:40 UTC Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.600 s 0.283
2023-01-16 15:07:21 UTC Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.987 s -0.011
2023-01-16 15:07:16 UTC Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.985 s 0.027
2023-01-16 15:07:34 UTC Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.942 s 0.311
2023-01-16 15:07:50 UTC Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.355 s 0.104
2023-01-16 15:08:26 UTC Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.499 s -0.061
2023-01-16 15:10:07 UTC Python file-write snappy, parquet, table, fanniemae_2016Q4 10.852 s -1.160
2023-01-16 15:09:33 UTC Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.019 s -0.041
2023-01-16 15:11:26 UTC Python file-write uncompressed, feather, table, fanniemae_2016Q4 4.611 s 2.570
2023-01-16 15:11:09 UTC Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.338 s -0.833
2023-01-16 15:12:09 UTC Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 13.649 s 2.523
2023-01-16 15:12:16 UTC Python file-write lz4, feather, table, fanniemae_2016Q4 1.558 s 2.427
2023-01-16 15:13:09 UTC Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.595 s 1.367
2023-01-16 15:12:49 UTC Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.579 s 2.570
2023-01-16 15:13:57 UTC Python file-write snappy, parquet, table, nyctaxi_2010-01 7.516 s 1.273
2023-01-16 15:13:32 UTC Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.081 s 1.400
2023-01-16 15:14:52 UTC Python file-write lz4, feather, table, nyctaxi_2010-01 1.388 s 2.853
2023-01-16 15:14:26 UTC Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.003 s 1.300
2023-01-16 15:14:34 UTC Python file-write uncompressed, feather, table, nyctaxi_2010-01 1.984 s 2.704
2023-01-16 15:14:46 UTC Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 3.383 s 2.920
2023-01-16 15:15:02 UTC Python file-write lz4, feather, dataframe, nyctaxi_2010-01 2.784 s 2.948
2023-01-16 15:15:08 UTC Python wide-dataframe use_legacy_dataset=false 0.506 s 1.013
2023-01-16 15:15:06 UTC Python wide-dataframe use_legacy_dataset=true 0.375 s 0.377
2023-01-16 15:39:39 UTC R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.316 s 0.245
2023-01-16 15:40:57 UTC R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.216 s 0.315
2023-01-16 15:41:17 UTC R file-read lz4, feather, table, nyctaxi_2010-01, R 0.590 s 0.270
2023-01-16 15:38:37 UTC R dataframe-to-table type_nested, R 0.575 s -0.640
2023-01-16 15:39:17 UTC R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.325 s -0.215
2023-01-16 15:39:05 UTC R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.568 s 0.075
2023-01-16 15:37:44 UTC R dataframe-to-table chi_traffic_2020_Q1, R 4.400 s -1.955
2023-01-16 15:39:58 UTC R file-read lz4, feather, table, fanniemae_2016Q4, R 0.608 s 0.226
2023-01-16 15:40:39 UTC R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.569 s -0.208
2023-01-16 15:38:06 UTC R dataframe-to-table type_dict, R 0.047 s 1.232
2023-01-16 15:41:27 UTC R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.905 s 0.276
2023-01-16 15:38:21 UTC R dataframe-to-table type_floats, R 0.013 s 0.620
2023-01-16 15:40:09 UTC R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.868 s 0.167
2023-01-16 15:40:29 UTC R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.909 s 0.006
2023-01-16 15:41:07 UTC R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.819 s 0.312
2023-01-16 15:37:59 UTC R dataframe-to-table type_strings, R 0.534 s 0.101
2023-01-16 15:38:14 UTC R dataframe-to-table type_integers, R 0.010 s 0.537
2023-01-16 15:38:51 UTC R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.315 s 0.108
2023-01-16 15:40:18 UTC R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.565 s -0.085
2023-01-16 15:39:30 UTC R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.576 s -0.169
2023-01-16 15:39:48 UTC R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.570 s 0.265
2023-01-16 15:40:49 UTC R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.914 s -0.084
2023-01-16 15:42:25 UTC R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.859 s -1.421
2023-01-16 15:44:18 UTC R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.883 s -1.735
2023-01-16 15:45:14 UTC R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.276 s -1.433
2023-01-16 15:47:09 UTC R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.327 s -1.679
2023-01-16 15:47:45 UTC R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.964 s -0.630
2023-01-16 15:49:16 UTC R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.187 s -3.017
2023-01-16 15:49:47 UTC R file-write lz4, feather, table, fanniemae_2016Q4, R 1.492 s 0.295
2023-01-16 15:51:12 UTC R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.579 s -1.551
2023-01-16 15:52:08 UTC R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.987 s -1.190
2023-01-16 15:53:13 UTC R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.782 s -0.852
2023-01-16 15:54:14 UTC R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.711 s -1.086
2023-01-16 15:55:26 UTC R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.746 s -0.998
2023-01-16 15:56:12 UTC R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.311 s -0.140
2023-01-16 15:57:07 UTC R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.179 s -0.472
2023-01-16 15:57:53 UTC R file-write lz4, feather, table, nyctaxi_2010-01, R 1.472 s -0.440
2023-01-16 15:59:18 UTC R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.258 s -0.814
2023-01-16 15:58:58 UTC R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.563 s -0.054
2023-01-16 15:59:53 UTC R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.201 s 0.225
2023-01-16 15:59:37 UTC R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.199 s 0.284
2023-01-16 15:59:45 UTC R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.239 s 0.283
2023-01-16 15:58:47 UTC R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.088 s -0.974
2023-01-16 15:59:11 UTC R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.603 s -0.945
2023-01-16 15:59:27 UTC R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.607 s -0.408
2023-01-16 16:00:01 UTC R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.280 s 0.247
2023-01-16 16:00:11 UTC R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.274 s 0.160
2023-01-16 16:00:20 UTC R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.590 s -0.141
2023-01-16 16:00:46 UTC R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.004 s 0.119
2023-01-16 16:01:14 UTC R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.280 s -0.055
2023-01-16 16:01:06 UTC R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.919 s -0.939
2023-01-16 16:01:48 UTC R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.335 s 0.217
2023-01-16 16:01:23 UTC R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.334 s 0.108
2023-01-16 16:01:40 UTC R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.349 s 0.135
2023-01-16 16:02:29 UTC R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.203
2023-01-16 16:01:57 UTC R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.430 s 0.277
2023-01-16 16:01:31 UTC R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.290 s 0.128
2023-01-16 16:02:10 UTC R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.668 s -1.221
2023-01-16 16:02:54 UTC R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.302 s 0.294
2023-01-16 16:02:21 UTC R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.068 s -0.701
2023-01-16 16:02:45 UTC R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.233 s 0.209
2023-01-16 16:03:04 UTC R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.303 s 0.015
2023-01-16 16:02:37 UTC R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.269 s 0.231
2023-01-16 16:04:01 UTC R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.555 s -0.275
2023-01-16 16:04:09 UTC R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.323
2023-01-16 16:03:13 UTC R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.588 s 0.089
2023-01-16 16:03:42 UTC R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.905 s -0.308
2023-01-16 16:04:17 UTC R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.232 s 0.337
2023-01-16 16:04:52 UTC R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.329 s 0.348
2023-01-16 16:04:25 UTC R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.201 s 0.271
2023-01-16 16:04:33 UTC R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.242 s 0.305
2023-01-16 16:04:43 UTC R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.272 s 0.157
2023-01-16 16:05:49 UTC R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.312 s 0.292
2023-01-16 16:05:20 UTC R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.926 s -0.361
2023-01-16 16:05:32 UTC R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.196 s -0.027
2023-01-16 16:05:57 UTC R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.266 s 0.189
2023-01-16 16:05:40 UTC R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.200
2023-01-16 16:06:16 UTC R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.325 s -0.074
2023-01-16 16:06:25 UTC R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.638 s 0.132
2023-01-16 16:06:06 UTC R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.351 s 0.236
2023-01-16 16:06:54 UTC R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.635 s -0.060
2023-01-16 16:07:21 UTC R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.183
2023-01-16 16:07:13 UTC R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.763 s -0.861
2023-01-16 16:07:29 UTC R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.201 s 0.265
2023-01-16 16:07:37 UTC R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.160 s 0.250
2023-01-16 16:08:04 UTC R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.512 s 0.096
2023-01-16 16:08:46 UTC R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.248 s 0.125
2023-01-16 16:08:54 UTC R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.344
2023-01-16 16:07:45 UTC R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.341
2023-01-16 16:09:30 UTC R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.351 s 0.243
2023-01-16 16:07:55 UTC R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.179 s 0.260
2023-01-16 16:09:02 UTC R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.337 s 0.416
2023-01-16 16:09:19 UTC R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.372 s 0.352
2023-01-16 16:08:28 UTC R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.354 s 0.191
2023-01-16 16:10:44 UTC R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.393 s 0.348
2023-01-16 16:09:11 UTC R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.293 s 0.335
2023-01-16 16:11:51 UTC R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.615 s 0.157
2023-01-16 16:12:11 UTC R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.774 s -0.114
2023-01-16 16:12:27 UTC R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.322 s 0.368
2023-01-16 16:12:44 UTC R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.369 s 0.371
2023-01-16 16:10:27 UTC R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.650 s -0.215
2023-01-16 16:12:35 UTC R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.295 s 0.343
2023-01-16 16:09:39 UTC R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.657 s 0.267
2023-01-16 16:10:08 UTC R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.788 s 0.046
2023-01-16 16:11:01 UTC R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.428 s 0.265
2023-01-16 16:12:55 UTC R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.442 s 0.098
2023-01-16 16:13:57 UTC R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.162 s -0.281
2023-01-16 16:12:19 UTC R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.271 s 0.357
2023-01-16 16:11:22 UTC R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.722 s 0.062
2023-01-16 16:10:53 UTC R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.339 s 0.261
2023-01-16 16:11:12 UTC R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.370 s 0.230
2023-01-16 16:10:36 UTC R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.333 s 0.302
2023-01-16 16:13:36 UTC R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.961 s -0.094
2023-01-16 16:14:14 UTC R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.298 s 0.316
2023-01-16 16:13:04 UTC R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.768 s 0.259
2023-01-16 16:14:22 UTC R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.259 s 0.222
2023-01-16 16:14:50 UTC R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.651 s 0.198
2023-01-16 16:14:06 UTC R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.256 s 0.131
2023-01-16 16:14:30 UTC R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.335 s 0.265
2023-01-16 16:14:41 UTC R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.322 s 0.090
2023-01-16 16:16:03 UTC R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.230 s 0.242
2023-01-16 16:15:55 UTC R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.260 s 0.267
2023-01-16 16:16:11 UTC R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.304 s 0.241
2023-01-16 16:15:19 UTC R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.877 s -0.056
2023-01-16 16:15:39 UTC R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.715 s 0.168
2023-01-16 16:16:20 UTC R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.330 s 0.110
2023-01-16 16:15:47 UTC R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.210 s 0.212
2023-01-16 16:16:29 UTC R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.542 s -0.053
2023-01-16 16:17:15 UTC R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.256 s 0.128
2023-01-16 16:16:59 UTC R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.296 s -1.071
2023-01-16 16:17:07 UTC R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s 0.146
2023-01-16 16:16:41 UTC R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.875 s -0.529
2023-01-16 16:17:43 UTC R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.494 s -1.277
2023-01-16 16:17:53 UTC R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.930 s -0.696
2023-01-16 16:17:24 UTC R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.306 s -0.330
2023-01-16 16:17:32 UTC R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.367 s 0.032
2023-01-16 16:18:28 UTC R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.691 s -2.454
2023-01-16 16:19:40 UTC R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.611 s -0.864
2023-01-16 16:19:05 UTC R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.183 s 0.178
2023-01-16 16:19:21 UTC R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.334 s -0.140
2023-01-16 16:19:30 UTC R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.431 s -0.131
2023-01-16 16:18:56 UTC R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.596 s -0.841
2023-01-16 16:19:13 UTC R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.239 s 0.041
2023-01-16 16:19:50 UTC R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.860 s -0.112
2023-01-16 16:20:12 UTC R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.453 s -2.504
2023-01-16 16:20:44 UTC R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.215 s 0.210
2023-01-16 16:20:36 UTC R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.547 s -0.756
2023-01-16 16:20:53 UTC R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.265 s 0.305
2023-01-16 16:21:01 UTC R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.242 s 0.188
2023-01-16 16:21:10 UTC R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.335 s 0.201
2023-01-16 16:21:20 UTC R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.444 s -0.127
2023-01-16 16:21:30 UTC R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.948 s -0.135
2023-01-16 16:21:59 UTC R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.603 s -1.224
2023-01-16 16:22:25 UTC R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 5.982 s -0.409
2023-01-16 16:22:35 UTC R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.208 s 0.322
2023-01-16 16:22:44 UTC R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.251 s 0.375
2023-01-16 16:23:00 UTC R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.284 s 0.312
2023-01-16 16:22:52 UTC R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.286
2023-01-16 16:23:12 UTC R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.230
2023-01-16 16:23:21 UTC R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.589 s 0.107
2023-01-16 16:24:04 UTC R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.579 s -0.017
2023-01-16 16:24:29 UTC R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.222 s 0.254
2023-01-16 16:23:45 UTC R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.625 s -0.282
2023-01-16 16:24:21 UTC R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.236 s 0.338
2023-01-16 16:24:37 UTC R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.284 s 0.292
2023-01-16 16:24:13 UTC R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.197 s 0.241
2023-01-16 16:24:46 UTC R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.329 s 0.029
2023-01-16 16:25:59 UTC R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.221 s 0.209
2023-01-16 16:25:40 UTC R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.217 s 0.265
2023-01-16 16:25:27 UTC R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.079 s 0.132
2023-01-16 16:24:56 UTC R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.527 s 0.211
2023-01-16 16:25:09 UTC R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.895 s -0.340
2023-01-16 16:25:51 UTC R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.267 s 0.280
2023-01-16 16:26:08 UTC R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.320 s 0.348
2023-01-16 16:26:18 UTC R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.259 s 0.241
2023-01-16 16:26:29 UTC R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.979 s -0.058
2023-01-16 16:26:55 UTC R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.667 s 0.091
2023-01-16 16:27:24 UTC R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.872 s -0.062
2023-01-16 16:27:49 UTC R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.209 s 0.265
2023-01-16 16:27:33 UTC R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.194 s 0.250
2023-01-16 16:27:41 UTC R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.241 s 0.304
2023-01-16 16:28:08 UTC R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.408 s -0.077
2023-01-16 16:27:57 UTC R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.264 s 0.265
2023-01-16 16:28:17 UTC R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.539 s 0.105
2023-01-16 16:28:54 UTC R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.495 s -1.601
2023-01-16 16:29:24 UTC R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s 0.102
2023-01-16 16:29:33 UTC R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.326 s 0.260
2023-01-16 16:29:16 UTC R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.365 s -0.920
2023-01-16 16:29:51 UTC R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.444 s 0.103
2023-01-16 16:29:42 UTC R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.443 s -0.101
2023-01-16 16:30:03 UTC R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.895 s -1.094
2023-01-16 16:30:15 UTC R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.335 s -0.264
2023-01-16 16:30:56 UTC R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.656 s -1.412
2023-01-16 16:31:33 UTC R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.476 s -1.970
2023-01-16 16:31:41 UTC R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.256 s 0.182
2023-01-16 16:31:58 UTC R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.258 s 0.063
2023-01-16 16:31:49 UTC R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.319 s 0.186
2023-01-16 16:32:07 UTC R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.370 s 0.210
2023-01-16 16:32:17 UTC R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.288 s 0.096
2023-01-16 16:32:28 UTC R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.965 s 0.104
2023-01-16 16:33:51 UTC R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.743 s -1.697
2023-01-16 16:34:01 UTC R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.806 s -0.513
2023-01-16 16:33:32 UTC R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.397 s -0.375
2023-01-16 16:32:55 UTC R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.607 s -0.183
2023-01-16 16:33:23 UTC R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.189 s -0.582
2023-01-16 16:33:41 UTC R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.454 s -0.151
2023-01-16 16:34:39 UTC R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.195 s -2.032
2023-01-16 16:34:21 UTC R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.903 s -1.340
2023-01-16 16:36:58 UTC R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.215 s -2.559
2023-01-16 16:38:48 UTC R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.041 s -1.603
2023-01-16 16:39:04 UTC R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.241 s 0.268
2023-01-16 16:39:20 UTC R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.260 s 0.274
2023-01-16 16:38:56 UTC R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.119
2023-01-16 16:39:29 UTC R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.229 s 0.115
2023-01-16 16:39:12 UTC R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.203 s 0.281
2023-01-16 16:39:50 UTC R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.310 s 0.053
2023-01-16 16:39:38 UTC R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.463 s -0.159
2023-01-16 16:40:05 UTC R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.335 s -0.191
2023-01-16 16:48:28 UTC JavaScript vectorFromArray numbers 0.016 s 0.048
2023-01-16 16:48:41 UTC JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.551
2023-01-16 16:48:29 UTC JavaScript Iterate Vector uint8Array 0.002 s 0.011
2023-01-16 16:48:37 UTC JavaScript toArray Vector booleans 0.010 s 0.465
2023-01-16 16:48:41 UTC JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.038 s 1.050
2023-01-16 16:48:29 UTC JavaScript vectorFromArray dictionary 0.017 s -0.103
2023-01-16 16:48:29 UTC JavaScript Iterate Vector uint16Array 0.002 s 0.374
2023-01-16 16:48:34 UTC JavaScript Spread Vector int32Array 0.007 s -0.179
2023-01-16 16:48:36 UTC JavaScript toArray Vector int32Array
2023-01-16 16:48:37 UTC JavaScript toArray Vector float32Array
2023-01-16 16:48:28 UTC JavaScript vectorFromArray booleans 0.018 s -0.040
2023-01-16 16:48:30 UTC JavaScript Iterate Vector int8Array 0.002 s 0.145
2023-01-16 16:48:30 UTC JavaScript Iterate Vector int32Array 0.002 s 0.252
2023-01-16 16:48:32 UTC JavaScript Iterate Vector dictionary 0.004 s 0.498
2023-01-16 16:48:41 UTC JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.474
2023-01-16 16:48:43 UTC JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-16 16:48:43 UTC JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-16 16:48:44 UTC JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.140
2023-01-16 16:48:36 UTC JavaScript toArray Vector int16Array
2023-01-16 16:48:38 UTC JavaScript toArray Vector string 0.146 s -0.036
2023-01-16 16:48:38 UTC JavaScript get Vector uint32Array 0.003 s 0.086
2023-01-16 16:48:39 UTC JavaScript get Vector int8Array 0.003 s -0.038
2023-01-16 16:48:39 UTC JavaScript get Vector float32Array 0.002 s -2.423
2023-01-16 16:48:30 UTC JavaScript Iterate Vector uint64Array 0.004 s 0.056
2023-01-16 16:48:30 UTC JavaScript Iterate Vector int16Array 0.002 s 0.013
2023-01-16 16:48:31 UTC JavaScript Iterate Vector float64Array 0.002 s 0.502
2023-01-16 16:48:31 UTC JavaScript Iterate Vector booleans 0.004 s 0.667
2023-01-16 16:48:32 UTC JavaScript Iterate Vector string 0.126 s 0.408
2023-01-16 16:48:35 UTC JavaScript toArray Vector uint16Array
2023-01-16 16:48:29 UTC JavaScript Iterate Vector uint32Array 0.002 s 0.379
2023-01-16 16:48:34 UTC JavaScript Spread Vector float32Array 0.008 s 0.172
2023-01-16 16:48:39 UTC JavaScript get Vector int16Array 0.003 s -0.289
2023-01-16 16:48:40 UTC JavaScript get Vector string 0.122 s 1.680
2023-01-16 16:48:43 UTC JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.187 s 0.507
2023-01-16 16:48:30 UTC JavaScript Iterate Vector int64Array 0.004 s 0.098
2023-01-16 16:48:33 UTC JavaScript Spread Vector uint64Array 0.012 s 0.105
2023-01-16 16:48:33 UTC JavaScript Spread Vector int16Array 0.006 s 0.381
2023-01-16 16:48:34 UTC JavaScript Spread Vector int64Array 0.012 s 0.038
2023-01-16 16:48:34 UTC JavaScript Spread Vector booleans 0.010 s 0.802
2023-01-16 16:48:31 UTC JavaScript Iterate Vector float32Array 0.002 s 0.506
2023-01-16 16:48:31 UTC JavaScript Iterate Vector numbers 0.002 s 0.489
2023-01-16 16:48:35 UTC JavaScript toArray Vector uint8Array
2023-01-16 16:48:36 UTC JavaScript toArray Vector int8Array
2023-01-16 16:48:41 UTC JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.072
2023-01-16 16:48:45 UTC JavaScript Table tracks, 1,000,000 0.095 s 0.181
2023-01-16 16:48:32 UTC JavaScript Spread Vector uint8Array 0.006 s 0.421
2023-01-16 16:48:33 UTC JavaScript Spread Vector uint32Array 0.007 s 0.179
2023-01-16 16:48:33 UTC JavaScript Spread Vector int8Array 0.006 s 0.055
2023-01-16 16:48:34 UTC JavaScript Spread Vector numbers 0.008 s 0.202
2023-01-16 16:48:35 UTC JavaScript toArray Vector uint32Array
2023-01-16 16:48:32 UTC JavaScript Spread Vector uint16Array 0.006 s 0.299
2023-01-16 16:48:34 UTC JavaScript Spread Vector float64Array 0.008 s 0.310
2023-01-16 16:48:35 UTC JavaScript Spread Vector string 0.145 s 0.113
2023-01-16 16:48:37 UTC JavaScript toArray Vector int64Array
2023-01-16 16:48:37 UTC JavaScript toArray Vector float64Array
2023-01-16 16:48:39 UTC JavaScript get Vector int32Array 0.003 s -0.356
2023-01-16 16:48:35 UTC JavaScript Spread Vector dictionary 0.010 s -1.128
2023-01-16 16:48:39 UTC JavaScript get Vector int64Array 0.003 s 0.160
2023-01-16 16:48:40 UTC JavaScript get Vector booleans 0.002 s 0.585
2023-01-16 16:48:42 UTC JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -1.922
2023-01-16 16:48:45 UTC JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s -0.657
2023-01-16 16:48:35 UTC JavaScript toArray Vector uint64Array
2023-01-16 16:48:38 UTC JavaScript get Vector uint16Array 0.003 s -0.051
2023-01-16 16:48:42 UTC JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s 0.946
2023-01-16 16:48:42 UTC JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.355
2023-01-16 16:48:37 UTC JavaScript toArray Vector numbers
2023-01-16 16:48:37 UTC JavaScript toArray Vector dictionary 0.010 s -0.828
2023-01-16 16:48:38 UTC JavaScript get Vector uint8Array 0.003 s -0.037
2023-01-16 16:48:39 UTC JavaScript get Vector uint64Array 0.003 s -0.028
2023-01-16 16:48:40 UTC JavaScript get Vector float64Array 0.002 s -0.088
2023-01-16 16:48:40 UTC JavaScript get Vector numbers 0.002 s 0.069
2023-01-16 16:48:44 UTC JavaScript Table tracks, 1,000,000 0.050 s 0.824
2023-01-16 16:48:44 UTC JavaScript Table 1,000,000, tracks 0.263 s 0.577
2023-01-16 16:48:45 UTC JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s -0.239
2023-01-16 16:48:40 UTC JavaScript get Vector dictionary 0.002 s -0.001
2023-01-16 16:48:40 UTC JavaScript Parse read recordBatches, tracks 0.000 s -0.034
2023-01-16 16:48:41 UTC JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.048
2023-01-16 16:48:46 UTC JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -1.381
2023-01-16 16:48:41 UTC JavaScript Parse write recordBatches, tracks 0.002 s -0.157
2023-01-16 16:48:41 UTC JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.526
2023-01-16 16:48:43 UTC JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.109 s -0.830
2023-01-16 16:48:44 UTC JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.542
2023-01-16 16:48:44 UTC JavaScript Table tracks, 1,000,000 0.271 s -0.004
2023-01-16 16:48:42 UTC JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -1.891
2023-01-16 16:48:43 UTC JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.189 s -0.609
2023-01-16 16:48:42 UTC JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.865
2023-01-16 16:48:43 UTC JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-16 16:48:43 UTC JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s