Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-13 15:27 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.582 s -2.517
2023-01-13 15:27 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.814 s -2.701
2023-01-13 15:28 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 13.436 s 0.887
2023-01-13 15:28 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 13.332 s 1.111
2023-01-13 15:29 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.443 s -0.706
2023-01-13 15:30 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 11.299 s -0.760
2023-01-13 15:29 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.131 s 0.117
2023-01-13 15:29 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 11.398 s -0.850
2023-01-13 15:32 Python dataframe-to-table type_strings 0.426 s 0.688
2023-01-13 15:32 Python dataset-filter nyctaxi_2010-01 1.021 s -0.284
2023-01-13 15:32 Python dataframe-to-table type_floats 0.010 s 0.225
2023-01-13 15:32 Python dataframe-to-table chi_traffic_2020_Q1 20.916 s 1.328
2023-01-13 15:32 Python dataframe-to-table type_integers 0.010 s 0.121
2023-01-13 15:32 Python dataframe-to-table type_dict 0.011 s -0.031
2023-01-13 15:32 Python dataframe-to-table type_nested 2.977 s 0.138
2023-01-13 15:37 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 84.101 s -0.366
2023-01-13 15:41 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 83.915 s -0.292
2023-01-13 15:52 Python dataset-read async=True, nyctaxi_multi_ipc_s3 219.517 s 0.550
2023-01-13 15:52 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.354 s -0.278
2023-01-13 15:52 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.195 s 0.266
2023-01-13 15:52 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.167 s 0.227
2023-01-13 15:53 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.236 s -4.317
2023-01-13 15:53 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.306 s -1.979
2023-01-13 15:52 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.301 s 0.178
2023-01-13 15:52 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.045 s 0.237
2023-01-13 15:53 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.040 s 0.234
2023-01-13 15:55 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.558 s -0.548
2023-01-13 15:53 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 3.801 s -5.460
2023-01-13 15:53 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.238 s -4.721
2023-01-13 15:53 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s -0.154
2023-01-13 15:53 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.268 s -2.916
2023-01-13 15:53 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s -1.043
2023-01-13 15:54 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.198 s 2.461
2023-01-13 15:54 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.932 s -2.749
2023-01-13 15:54 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.282
2023-01-13 15:53 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.761 s -0.619
2023-01-13 15:58 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.278 s -2.663
2023-01-13 15:58 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.151 s -0.164
2023-01-13 16:07 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.045 s -2.926
2023-01-13 15:58 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.150 s -0.309
2023-01-13 16:22 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.942 s -0.118
2023-01-13 16:22 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.940 s 0.289
2023-01-13 16:06 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.026 s -0.964
2023-01-13 16:22 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.970 s 0.114
2023-01-13 16:26 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.348 s -0.157
2023-01-13 16:21 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.629 s -0.004
2023-01-13 16:07 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.225 s 1.100
2023-01-13 16:06 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.320 s -0.550
2023-01-13 16:07 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.225 s 0.122
2023-01-13 16:06 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.286 s -2.271
2023-01-13 16:08 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.724 s -0.486
2023-01-13 16:22 Python file-read lz4, feather, table, nyctaxi_2010-01 0.677 s 0.290
2023-01-13 16:22 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.911 s 0.273
2023-01-13 16:11 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.411 s -0.272
2023-01-13 16:22 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.203 s 0.806
2023-01-13 16:22 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.585 s 0.311
2023-01-13 16:26 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.452 s -1.713
2023-01-13 16:06 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.869 s -0.336
2023-01-13 16:11 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.854 s -2.829
2023-01-13 16:30 Python wide-dataframe use_legacy_dataset=true 0.376 s 0.226
2023-01-13 16:21 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.496 s 0.087
2023-01-13 16:06 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s 0.147
2023-01-13 16:21 Python file-read lz4, feather, table, fanniemae_2016Q4 0.805 s 0.527
2023-01-13 16:25 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.932 s -2.638
2023-01-13 16:41 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.837 s 0.326
2023-01-13 16:23 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.719 s -2.056
2023-01-13 16:11 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.408 s -0.429
2023-01-13 16:20 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.607 s -0.480
2023-01-13 16:22 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.983 s -0.073
2023-01-13 16:24 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.331 s -1.878
2023-01-13 16:29 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.719 s -0.072
2023-01-13 16:39 R dataframe-to-table type_integers, R 0.010 s 0.001
2023-01-13 16:22 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.340 s 0.218
2023-01-13 16:27 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.925 s 0.084
2023-01-13 16:39 R dataframe-to-table type_nested, R 0.575 s -0.614
2023-01-13 16:40 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.579 s -0.432
2023-01-13 16:20 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.647 s 0.043
2023-01-13 16:30 Python wide-dataframe use_legacy_dataset=false 0.512 s 0.448
2023-01-13 16:21 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.500 s -0.206
2023-01-13 16:27 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.261 s -0.088
2023-01-13 16:21 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.311 s 0.369
2023-01-13 16:40 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.333 s -0.626
2023-01-13 16:40 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.603 s -1.233
2023-01-13 16:21 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.626 s 0.398
2023-01-13 16:27 Python file-write lz4, feather, table, fanniemae_2016Q4 1.852 s -0.077
2023-01-13 16:28 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 6.006 s -1.665
2023-01-13 16:29 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.870 s -1.892
2023-01-13 16:30 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.115 s -0.024
2023-01-13 16:30 Python file-write lz4, feather, table, nyctaxi_2010-01 1.779 s 0.101
2023-01-13 16:39 R dataframe-to-table type_dict, R 0.045 s 1.801
2023-01-13 16:30 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.194 s -0.004
2023-01-13 16:39 R dataframe-to-table type_strings, R 0.533 s 0.366
2023-01-13 16:28 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.517 s -2.117
2023-01-13 16:29 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.394 s -2.154
2023-01-13 16:39 R dataframe-to-table chi_traffic_2020_Q1, R 4.435 s -3.345
2023-01-13 16:39 R dataframe-to-table type_floats, R 0.013 s 0.687
2023-01-13 16:40 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.324 s -0.210
2023-01-13 16:40 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.314 s 0.234
2023-01-13 16:41 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.917 s -0.284
2023-01-13 16:41 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.566 s 0.273
2023-01-13 16:42 R file-read lz4, feather, table, nyctaxi_2010-01, R 1.264 s -2.354
2023-01-13 16:41 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.587 s 0.356
2023-01-13 16:41 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.566 s -0.226
2023-01-13 16:41 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.571 s -0.408
2023-01-13 16:42 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.920 s -0.403
2023-01-13 16:43 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.905 s 0.266
2023-01-13 16:42 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.216 s 0.345
2023-01-13 16:42 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 1.595 s -1.683
2023-01-13 16:43 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.894 s -2.659
2023-01-13 16:45 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.872 s -2.578
2023-01-13 16:46 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.310 s -2.634
2023-01-13 16:49 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.962 s -0.473
2023-01-13 16:48 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.382 s -3.002
2023-01-13 16:50 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.023 s 0.255
2023-01-13 16:51 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.495 s -0.553
2023-01-13 17:03 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.431 s 0.228
2023-01-13 16:52 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.520 s -0.432
2023-01-13 16:53 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 5.082 s -3.350
2023-01-13 17:00 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.552 s 0.492
2023-01-13 17:01 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.204 s -0.087
2023-01-13 17:08 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.632 s 0.283
2023-01-13 17:09 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.159 s 0.306
2023-01-13 17:11 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.229 s 0.122
2023-01-13 16:54 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.909 s -3.236
2023-01-13 16:55 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.821 s -3.356
2023-01-13 17:02 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 0.997 s 0.824
2023-01-13 17:04 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.268 s 0.228
2023-01-13 17:07 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.330 s 0.268
2023-01-13 17:12 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.776 s 0.444
2023-01-13 17:13 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.427 s 0.190
2023-01-13 17:18 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.229 s 0.241
2023-01-13 17:19 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.252 s 0.330
2023-01-13 17:00 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.248 s 0.737
2023-01-13 17:01 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.274 s 0.034
2023-01-13 17:11 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.289 s 0.293
2023-01-13 17:17 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.874 s 0.508
2023-01-13 16:57 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.309 s 0.455
2023-01-13 17:01 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.601 s -0.273
2023-01-13 17:10 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.233 s 0.358
2023-01-13 17:12 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.539 s 0.322
2023-01-13 17:16 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.259 s 0.181
2023-01-13 17:24 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.529 s 0.109
2023-01-13 16:57 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.863 s -3.276
2023-01-13 17:01 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.280 s 0.188
2023-01-13 17:06 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.258 s -3.053
2023-01-13 17:10 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.178 s 0.296
2023-01-13 17:13 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.714 s 0.131
2023-01-13 17:14 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.616 s -0.034
2023-01-13 17:08 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.312 s 0.301
2023-01-13 17:01 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.200 s 0.234
2023-01-13 17:03 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.333 s 0.143
2023-01-13 17:03 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.289 s 0.148
2023-01-13 17:04 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.231 s 0.238
2023-01-13 16:59 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.468 s 0.945
2023-01-13 17:18 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.260 s 0.240
2023-01-13 17:18 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.303 s 0.237
2023-01-13 17:19 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.861 s 0.471
2023-01-13 17:22 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.291 s 0.544
2023-01-13 17:22 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.523 s -1.162
2023-01-13 17:25 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.580 s 0.226
2023-01-13 17:29 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.564 s 0.749
2023-01-13 17:02 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.631 s 0.912
2023-01-13 17:08 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.265 s 0.204
2023-01-13 17:11 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.350 s 0.224
2023-01-13 16:58 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.176 s -0.482
2023-01-13 17:01 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.239 s 0.222
2023-01-13 17:01 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.580 s 0.241
2023-01-13 17:04 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.302 s 0.231
2023-01-13 17:04 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.301 s 0.080
2023-01-13 17:10 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.502 s 0.302
2023-01-13 17:11 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.292 s 0.258
2023-01-13 17:00 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.094 s -1.419
2023-01-13 17:07 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.260 s 0.234
2023-01-13 17:10 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.350 s 0.319
2023-01-13 17:11 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.372 s 0.297
2023-01-13 17:16 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.255 s 0.175
2023-01-13 17:18 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.328 s 0.184
2023-01-13 17:19 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s -0.013
2023-01-13 17:31 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.438 s 0.339
2023-01-13 17:00 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.606 s -1.256
2023-01-13 17:02 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.279 s 0.041
2023-01-13 17:03 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.646 s 0.584
2023-01-13 17:21 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.114 s 0.389
2023-01-13 17:23 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.334 s 0.152
2023-01-13 17:27 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.266 s 0.239
2023-01-13 17:03 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.348 s 0.203
2023-01-13 17:04 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.580 s 0.265
2023-01-13 17:06 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.344 s -5.270
2023-01-13 17:03 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.334 s 0.262
2023-01-13 17:09 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.160 s 0.209
2023-01-13 17:13 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.338 s 0.249
2023-01-13 17:16 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.298 s 0.300
2023-01-13 17:13 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.369 s 0.202
2023-01-13 17:19 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.301 s 0.015
2023-01-13 17:30 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.531 s 0.304
2023-01-13 17:06 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.200 s 0.250
2023-01-13 17:14 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.670 s 0.397
2023-01-13 17:23 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.241 s 0.071
2023-01-13 17:23 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.439 s 0.105
2023-01-13 17:26 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.521 s 0.371
2023-01-13 17:03 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.036 s 0.388
2023-01-13 17:04 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.228 s 0.186
2023-01-13 17:06 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.270 s 0.181
2023-01-13 17:07 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.197 s -0.180
2023-01-13 17:08 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.325 s -0.098
2023-01-13 17:11 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.651 s 0.315
2023-01-13 17:14 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.295 s 0.293
2023-01-13 17:24 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.208 s 0.279
2023-01-13 17:06 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.829 s -3.733
2023-01-13 17:09 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.631 s 0.135
2023-01-13 17:16 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.337 s 0.199
2023-01-13 17:18 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.529 s 0.346
2023-01-13 17:05 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.925 s -1.340
2023-01-13 17:06 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.241 s 0.279
2023-01-13 17:07 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.911 s 0.238
2023-01-13 17:09 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.201 s 0.255
2023-01-13 17:14 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.377 s -1.187
2023-01-13 17:17 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.650 s 0.171
2023-01-13 17:20 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.871 s 0.157
2023-01-13 17:26 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.613 s 0.195
2023-01-13 17:27 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.034 s 0.401
2023-01-13 17:08 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.349 s 0.247
2023-01-13 17:09 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.619 s 0.673
2023-01-13 17:23 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.266 s 0.111
2023-01-13 17:11 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.337 s 0.349
2023-01-13 17:12 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.333 s 0.183
2023-01-13 17:12 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.393 s 0.246
2023-01-13 17:15 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.763 s 0.339
2023-01-13 17:15 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 0.956 s 0.077
2023-01-13 17:18 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.696 s 0.133
2023-01-13 17:21 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.182 s 0.243
2023-01-13 17:21 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.329 s 0.188
2023-01-13 17:21 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.424 s -0.094
2023-01-13 17:27 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.521 s 0.342
2023-01-13 17:29 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.209 s 0.216
2023-01-13 17:14 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.279 s -0.108
2023-01-13 17:15 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.371 s 0.205
2023-01-13 17:19 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.358 s 0.426
2023-01-13 17:22 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.588 s 0.323
2023-01-13 17:25 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.252 s 0.261
2023-01-13 17:25 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.242 s 0.156
2023-01-13 17:33 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.197 s 0.469
2023-01-13 17:15 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.440 s 0.155
2023-01-13 17:31 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.228 s 0.274
2023-01-13 17:16 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.062 s 0.285
2023-01-13 17:19 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.266 s -1.180
2023-01-13 17:24 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 5.664 s 0.684
2023-01-13 17:25 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.211 s 0.173
2023-01-13 17:25 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.283 s 0.237
2023-01-13 17:26 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.283 s 0.302
2023-01-13 17:29 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.666 s 0.061
2023-01-13 17:33 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.256 s 0.156
2023-01-13 17:17 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.322 s 0.079
2023-01-13 17:27 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.881 s 0.269
2023-01-13 17:27 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.215 s 0.245
2023-01-13 17:28 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.219 s 0.191
2023-01-13 17:18 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.209 s 0.174
2023-01-13 17:30 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.263 s 0.238
2023-01-13 17:31 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.324 s 0.284
2023-01-13 17:32 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.312 s 0.393
2023-01-13 17:33 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.594 s 0.996
2023-01-13 17:23 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.215 s -0.029
2023-01-13 17:28 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.258 s 0.180
2023-01-13 17:31 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.435 s 0.374
2023-01-13 17:33 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.319 s 0.191
2023-01-13 17:20 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.472 s 0.475
2023-01-13 17:22 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.861 s -0.687
2023-01-13 17:20 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.520 s 1.144
2023-01-13 17:21 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.235 s 0.059
2023-01-13 17:23 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 0.922 s 0.187
2023-01-13 17:26 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.195 s 0.299
2023-01-13 17:26 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.236 s 0.320
2023-01-13 17:26 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.220 s 0.323
2023-01-13 17:27 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.323 s 0.305
2023-01-13 17:28 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.319 s 0.278
2023-01-13 17:28 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.961 s 0.040
2023-01-13 17:29 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.193 s 0.304
2023-01-13 17:29 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.242 s 0.241
2023-01-13 17:30 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.403 s 0.251
2023-01-13 17:30 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.433 s 0.662
2023-01-13 17:31 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.271 s 0.212
2023-01-13 17:32 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.888 s -0.321
2023-01-13 17:34 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.257 s 0.172
2023-01-13 17:34 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.369 s 0.266
2023-01-13 17:34 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.991 s -0.484
2023-01-13 17:34 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.287 s 0.178
2023-01-13 17:35 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.393 s 0.192
2023-01-13 17:34 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.605 s -0.057
2023-01-13 17:38 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 29.735 s 0.685
2023-01-13 17:35 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 5.892 s 0.521
2023-01-13 17:35 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.452 s -0.122
2023-01-13 17:35 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.726 s 0.284
2023-01-13 17:36 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.790 s 0.075
2023-01-13 17:36 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.863 s 0.498
2023-01-13 17:36 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.105 s 0.611
2023-01-13 17:40 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.197 s 0.093
2023-01-13 17:40 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 32.364 s 0.862
2023-01-13 17:41 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.203 s 0.244
2023-01-13 17:41 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.259 s 0.249
2023-01-13 17:42 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.273 s 0.376
2023-01-13 17:41 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.447 s 0.296
2023-01-13 17:50 JavaScript Spread Vector int64Array 0.012 s -0.424
2023-01-13 17:50 JavaScript toArray Vector int16Array
2023-01-13 17:41 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.241 s 0.230
2023-01-13 17:50 JavaScript toArray Vector uint32Array
2023-01-13 17:50 JavaScript toArray Vector int8Array
2023-01-13 17:50 JavaScript toArray Vector float32Array
2023-01-13 17:50 JavaScript Spread Vector uint16Array 0.007 s 0.029
2023-01-13 17:50 JavaScript Spread Vector uint64Array 0.012 s -0.239
2023-01-13 17:50 JavaScript Spread Vector float64Array 0.008 s 0.760
2023-01-13 17:41 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.226 s 0.231
2023-01-13 17:50 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.520
2023-01-13 17:50 JavaScript Spread Vector dictionary 0.010 s 0.368
2023-01-13 17:50 JavaScript toArray Vector uint8Array
2023-01-13 17:50 JavaScript toArray Vector int32Array
2023-01-13 17:50 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.557
2023-01-13 17:50 JavaScript Spread Vector int16Array 0.007 s -0.051
2023-01-13 17:50 JavaScript Spread Vector booleans 0.010 s -0.637
2023-01-13 17:50 JavaScript toArray Vector uint16Array
2023-01-13 17:50 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.184 s 1.424
2023-01-13 17:50 JavaScript Iterate Vector uint32Array 0.002 s -1.001
2023-01-13 17:50 JavaScript Spread Vector string 0.146 s -0.358
2023-01-13 17:50 JavaScript vectorFromArray booleans 0.018 s -0.081
2023-01-13 17:41 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.308 s 0.145
2023-01-13 17:50 JavaScript toArray Vector string 0.146 s -0.172
2023-01-13 17:50 JavaScript vectorFromArray numbers 0.016 s -0.537
2023-01-13 17:50 JavaScript vectorFromArray dictionary 0.016 s 1.137
2023-01-13 17:50 JavaScript Iterate Vector uint16Array 0.002 s -0.004
2023-01-13 17:50 JavaScript Iterate Vector uint64Array 0.004 s -0.273
2023-01-13 17:50 JavaScript Iterate Vector int16Array 0.002 s -0.169
2023-01-13 17:50 JavaScript Iterate Vector int64Array 0.005 s -0.268
2023-01-13 17:50 JavaScript Iterate Vector uint8Array 0.002 s -1.289
2023-01-13 17:50 JavaScript Iterate Vector float32Array 0.002 s -0.186
2023-01-13 17:50 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.965
2023-01-13 17:50 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.347
2023-01-13 17:50 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-13 17:50 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.560
2023-01-13 17:50 JavaScript Table tracks, 1,000,000 0.095 s 0.158
2023-01-13 17:50 JavaScript Iterate Vector int8Array 0.002 s -2.189
2023-01-13 17:50 JavaScript Iterate Vector int32Array 0.002 s -0.402
2023-01-13 17:50 JavaScript Iterate Vector numbers 0.002 s 0.331
2023-01-13 17:50 JavaScript Iterate Vector dictionary 0.004 s -0.332
2023-01-13 17:50 JavaScript Spread Vector uint8Array 0.007 s 0.106
2023-01-13 17:50 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.187 s 0.659
2023-01-13 17:50 JavaScript Iterate Vector float64Array 0.002 s 0.383
2023-01-13 17:50 JavaScript Iterate Vector booleans 0.004 s -0.551
2023-01-13 17:50 JavaScript Iterate Vector string 0.124 s 1.311
2023-01-13 17:50 JavaScript toArray Vector int64Array
2023-01-13 17:50 JavaScript get Vector string 0.124 s 0.625
2023-01-13 17:50 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-13 17:50 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.711
2023-01-13 17:50 JavaScript Table tracks, 1,000,000 0.050 s -1.096
2023-01-13 17:50 JavaScript Spread Vector uint32Array 0.007 s 0.841
2023-01-13 17:50 JavaScript Spread Vector int8Array 0.006 s 0.371
2023-01-13 17:50 JavaScript Spread Vector int32Array 0.006 s 0.579
2023-01-13 17:50 JavaScript Spread Vector float32Array 0.008 s 0.360
2023-01-13 17:50 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.068
2023-01-13 17:50 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-13 17:50 JavaScript Spread Vector numbers 0.008 s 0.479
2023-01-13 17:50 JavaScript get Vector uint8Array 0.003 s -0.047
2023-01-13 17:50 JavaScript get Vector int32Array 0.003 s -0.196
2023-01-13 17:50 JavaScript get Vector float32Array 0.002 s -0.831
2023-01-13 17:50 JavaScript get Vector numbers 0.002 s 0.249
2023-01-13 17:50 JavaScript toArray Vector uint64Array
2023-01-13 17:50 JavaScript get Vector uint16Array 0.003 s -0.048
2023-01-13 17:50 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.264
2023-01-13 17:50 JavaScript Table 1,000,000, tracks 0.297 s -1.101
2023-01-13 17:50 JavaScript toArray Vector float64Array
2023-01-13 17:50 JavaScript toArray Vector booleans 0.010 s -0.817
2023-01-13 17:50 JavaScript Parse write recordBatches, tracks 0.002 s 0.888
2023-01-13 17:50 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.657
2023-01-13 17:50 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.712
2023-01-13 17:50 JavaScript toArray Vector numbers
2023-01-13 17:50 JavaScript toArray Vector dictionary 0.010 s -0.717
2023-01-13 17:50 JavaScript get Vector uint32Array 0.003 s -0.066
2023-01-13 17:50 JavaScript get Vector int8Array 0.003 s -0.007
2023-01-13 17:50 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s 0.942
2023-01-13 17:50 JavaScript get Vector uint64Array 0.003 s -0.350
2023-01-13 17:50 JavaScript get Vector int16Array 0.003 s -0.065
2023-01-13 17:50 JavaScript get Vector int64Array 0.003 s -0.244
2023-01-13 17:50 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.586
2023-01-13 17:50 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.040 s -0.074
2023-01-13 17:50 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -1.327
2023-01-13 17:50 JavaScript get Vector float64Array 0.002 s 0.207
2023-01-13 17:50 JavaScript get Vector booleans 0.002 s 0.642
2023-01-13 17:50 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.100
2023-01-13 17:50 JavaScript get Vector dictionary 0.002 s 0.321
2023-01-13 17:50 JavaScript Parse read recordBatches, tracks 0.000 s -0.069
2023-01-13 17:50 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-13 17:50 JavaScript Table tracks, 1,000,000 0.274 s -0.201
2023-01-13 17:50 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.454
2023-01-13 17:50 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -1.065