Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2023-01-14 22:19 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.230 s 0.338
2023-01-14 22:19 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.786 s -0.308
2023-01-14 22:20 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.078 s -1.203
2023-01-14 22:21 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.432 s 0.809
2023-01-14 22:21 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.062 s -1.273
2023-01-14 22:21 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.128 s 0.155
2023-01-14 22:22 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 10.474 s 1.161
2023-01-14 22:22 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 10.500 s 1.255
2023-01-14 22:24 Python dataframe-to-table type_floats 0.010 s 0.162
2023-01-14 22:24 Python dataframe-to-table type_integers 0.010 s -1.816
2023-01-14 22:25 Python dataframe-to-table type_nested 2.994 s -0.669
2023-01-14 22:24 Python dataframe-to-table type_strings 0.429 s -0.598
2023-01-14 22:24 Python dataframe-to-table chi_traffic_2020_Q1 20.961 s 1.007
2023-01-14 22:24 Python dataframe-to-table type_dict 0.011 s 0.763
2023-01-14 22:25 Python dataset-filter nyctaxi_2010-01 1.026 s -0.255
2023-01-14 22:45 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.203 s -0.134
2023-01-14 22:44 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.246 s -0.097
2023-01-14 22:44 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.039 s 0.232
2023-01-14 22:45 Python dataset-serialize csv, 1pc, nyctaxi_multi_parquet_s3 0.758 s 0.170
2023-01-14 22:44 Python dataset-read async=True, nyctaxi_multi_ipc_s3 222.338 s 0.002
2023-01-14 22:45 Python dataset-serialize arrow, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.547
2023-01-14 23:21 Python file-write uncompressed, feather, table, nyctaxi_2010-01 2.742 s -0.036
2023-01-14 23:52 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.596 s -0.862
2023-01-14 22:45 Python dataset-serialize arrow, 10pc, nyctaxi_multi_parquet_s3 0.199 s 0.337
2023-01-14 22:58 Python dataset-serialize arrow, 1pc, nyctaxi_multi_ipc_s3 0.026 s -1.071
2023-01-14 23:13 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.625 s 0.372
2023-01-14 23:13 Python file-read lz4, feather, table, fanniemae_2016Q4 0.820 s 0.189
2023-01-14 23:13 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.983 s -0.048
2023-01-14 23:14 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.933 s 0.341
2023-01-14 22:45 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.676 s 0.178
2023-01-14 22:45 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.175 s -0.790
2023-01-14 22:58 Python dataset-serialize parquet, 1pc, nyctaxi_multi_ipc_s3 0.288 s -2.492
2023-01-14 23:20 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.401 s -1.151
2023-01-14 23:21 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.255 s -0.893
2023-01-14 23:33 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 0.908 s -0.069
2023-01-14 22:44 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.009 s 0.324
2023-01-14 22:59 Python dataset-serialize csv, 10pc, nyctaxi_multi_ipc_s3 8.695 s 0.556
2023-01-14 23:12 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.499 s 0.105
2023-01-14 23:13 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.320 s 0.341
2023-01-14 23:13 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.965 s 0.205
2023-01-14 23:14 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.958 s -0.259
2023-01-14 23:14 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.334 s 0.281
2023-01-14 22:33 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 83.689 s -0.052
2023-01-14 22:44 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.833 s -3.831
2023-01-14 22:44 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.311 s 0.120
2023-01-14 22:58 Python dataset-serialize feather, 10pc, nyctaxi_multi_ipc_s3 0.224 s 0.945
2023-01-14 23:12 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.639 s 0.215
2023-01-14 23:12 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.506 s -0.292
2023-01-14 23:14 Python file-read lz4, feather, table, nyctaxi_2010-01 0.676 s 0.284
2023-01-14 23:19 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.900 s 0.311
2023-01-14 23:22 Python wide-dataframe use_legacy_dataset=false 0.515 s 0.183
2023-01-14 23:31 R dataframe-to-table type_integers, R 0.010 s 0.629
2023-01-14 23:31 R dataframe-to-table type_nested, R 0.571 s 0.811
2023-01-14 23:32 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.313 s 0.237
2023-01-14 22:28 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 72.178 s 1.008
2023-01-14 22:58 Python dataset-serialize arrow, 10pc, nyctaxi_multi_ipc_s3 0.226 s -0.526
2023-01-14 23:03 Python dataset-serialize parquet, 100pc, nyctaxi_multi_ipc_s3 30.905 s -2.377
2023-01-14 23:15 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.697 s -1.673
2023-01-14 23:16 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 20.233 s -1.188
2023-01-14 23:19 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.892 s -0.813
2023-01-14 23:20 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.777 s -1.030
2023-01-14 23:31 R dataframe-to-table type_dict, R 0.047 s 1.214
2023-01-14 23:32 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 0.566 s 0.267
2023-01-14 23:34 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 0.898 s 0.286
2023-01-14 23:45 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.982 s -1.457
2023-01-14 23:47 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.711 s -1.394
2023-01-14 23:52 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.01, R 0.201 s 0.151
2023-01-14 23:52 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=0.1, R 0.205 s -0.088
2023-01-14 23:52 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.1, R 0.283 s 0.113
2023-01-14 23:54 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=10, R 3.709 s 0.448
2023-01-14 22:44 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.217 s -0.125
2023-01-14 22:46 Python dataset-serialize csv, 10pc, nyctaxi_multi_parquet_s3 7.537 s 0.254
2023-01-14 22:49 Python dataset-serialize parquet, 100pc, nyctaxi_multi_parquet_s3 30.304 s -2.320
2023-01-14 22:50 Python dataset-serialize feather, 100pc, nyctaxi_multi_parquet_s3 2.152 s -0.634
2023-01-14 22:58 Python dataset-serialize csv, 100pc, nyctaxi_multi_parquet_s3 76.066 s 0.382
2023-01-14 22:58 Python dataset-serialize parquet, 10pc, nyctaxi_multi_ipc_s3 3.046 s -2.259
2023-01-14 23:12 Python dataset-serialize csv, 100pc, nyctaxi_multi_ipc_s3 86.299 s 0.574
2023-01-14 23:12 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.626 s 0.097
2023-01-14 23:18 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 15.301 s -0.052
2023-01-14 23:21 Python file-write lz4, feather, table, nyctaxi_2010-01 1.765 s 0.245
2023-01-14 23:32 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.570 s -0.049
2023-01-14 22:45 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.135 s -0.128
2023-01-14 22:45 Python dataset-serialize parquet, 1pc, nyctaxi_multi_parquet_s3 0.306 s -2.110
2023-01-14 22:45 Python dataset-serialize feather, 1pc, nyctaxi_multi_parquet_s3 0.023 s 0.538
2023-01-14 22:45 Python dataset-serialize parquet, 10pc, nyctaxi_multi_parquet_s3 2.929 s -1.859
2023-01-14 22:45 Python dataset-serialize feather, 10pc, nyctaxi_multi_parquet_s3 0.199 s 1.330
2023-01-14 22:50 Python dataset-serialize arrow, 100pc, nyctaxi_multi_parquet_s3 2.150 s -0.075
2023-01-14 22:58 Python dataset-serialize feather, 1pc, nyctaxi_multi_ipc_s3 0.025 s 1.170
2023-01-14 22:58 Python dataset-serialize csv, 1pc, nyctaxi_multi_ipc_s3 0.866 s 0.759
2023-01-14 23:03 Python dataset-serialize arrow, 100pc, nyctaxi_multi_ipc_s3 2.402 s 1.577
2023-01-14 23:03 Python dataset-serialize feather, 100pc, nyctaxi_multi_ipc_s3 2.410 s -0.102
2023-01-14 23:13 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.206 s 0.639
2023-01-14 23:14 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.955 s -0.236
2023-01-14 23:14 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.587 s 0.321
2023-01-14 23:16 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.878 s -1.791
2023-01-14 23:17 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 20.407 s -1.341
2023-01-14 23:18 Python file-write uncompressed, feather, table, fanniemae_2016Q4 6.424 s -0.197
2023-01-14 23:19 Python file-write lz4, feather, table, fanniemae_2016Q4 1.834 s 0.244
2023-01-14 23:21 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 4.134 s 0.037
2023-01-14 23:22 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.221 s -0.068
2023-01-14 23:32 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.318 s -0.051
2023-01-14 23:33 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 0.846 s 0.257
2023-01-14 23:33 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 0.913 s -0.158
2023-01-14 23:40 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 17.290 s -1.856
2023-01-14 23:52 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=0.01, R 0.241 s 0.169
2023-01-14 23:56 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=1, R 0.589 s -0.063
2023-01-14 23:57 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.01, R 0.234 s 0.192
2023-01-14 23:58 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.1, R 0.352 s 0.154
2023-01-15 00:00 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=10, R 3.788 s -1.737
2023-01-15 00:09 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=1, R 0.323 s 0.033
2023-01-15 00:12 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=1, R 0.918 s -0.859
2023-01-15 00:14 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.1, R 0.335 s -0.348
2023-01-15 00:14 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=1, R 0.865 s -0.602
2023-01-15 00:15 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=10, R 5.515 s -0.759
2023-01-15 00:16 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.1, R 0.480 s -4.523
2023-01-15 00:16 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=1, R 0.510 s -5.664
2023-01-15 00:21 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=1, R 0.259 s 0.140
2023-01-15 00:22 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=1, R 0.987 s -0.435
2023-01-15 00:25 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=1, R 0.891 s -0.714
2023-01-14 23:22 Python wide-dataframe use_legacy_dataset=true 0.379 s -0.009
2023-01-14 23:54 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.01, R 0.281 s -0.217
2023-01-14 23:55 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=10, R 0.685 s -4.005
2023-01-14 23:55 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.01, R 0.229 s 0.107
2023-01-14 23:59 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=1, R 0.644 s -0.104
2023-01-14 23:30 R dataframe-to-table type_strings, R 0.533 s 0.603
2023-01-14 23:30 R dataframe-to-table chi_traffic_2020_Q1, R 4.247 s 0.281
2023-01-14 23:31 R dataframe-to-table type_floats, R 0.013 s 0.686
2023-01-14 23:31 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.316 s 0.118
2023-01-14 23:32 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.592 s 0.314
2023-01-14 23:33 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 0.564 s -0.156
2023-01-14 23:46 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.772 s -1.031
2023-01-14 23:54 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.1, R 0.350 s 0.102
2023-01-14 23:55 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.01, R 0.270 s 0.137
2023-01-14 23:55 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=1, R 0.301 s 0.103
2023-01-14 23:58 R tpch arrow, parquet, memory_map=False, TPCH-05, scale_factor=0.01, R 0.314 s 0.221
2023-01-15 00:00 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.1, R 0.234 s 0.305
2023-01-15 00:01 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.01, R 0.291 s 0.258
2023-01-15 00:02 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.1, R 0.374 s 0.244
2023-01-15 00:08 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=10, R 4.311 s -1.701
2023-01-15 00:09 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.01, R 0.299 s 0.289
2023-01-15 00:11 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=10, R 3.250 s -0.975
2023-01-15 00:14 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.01, R 0.241 s -0.159
2023-01-15 00:18 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=1, R 0.243 s 0.090
2023-01-15 00:21 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=10, R 3.098 s -0.176
2023-01-15 00:22 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=10, R 0.666 s 0.047
2023-01-15 00:23 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.01, R 0.195 s 0.130
2023-01-15 00:24 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.01, R 0.274 s -0.061
2023-01-14 23:32 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.578 s -0.350
2023-01-14 23:34 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.582 s 0.285
2023-01-14 23:50 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.159 s 0.285
2023-01-14 23:54 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=1, R 0.434 s 0.093
2023-01-14 23:56 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=10, R 3.531 s -0.335
2023-01-14 23:57 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.1, R 0.203 s 0.107
2023-01-14 23:58 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=10, R 0.922 s -0.263
2023-01-14 23:59 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=1, R 0.325 s -0.125
2023-01-15 00:00 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.1, R 0.161 s 0.226
2023-01-15 00:02 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=1, R 0.353 s 0.102
2023-01-15 00:03 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=10, R 0.788 s -0.144
2023-01-15 00:04 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.01, R 0.541 s -4.326
2023-01-15 00:08 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=10, R 1.018 s -4.048
2023-01-15 00:09 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.01, R 0.255 s 0.186
2023-01-15 00:09 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=0.1, R 0.261 s 0.095
2023-01-15 00:12 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.1, R 0.369 s -0.190
2023-01-15 00:19 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.01, R 0.197 s 0.206
2023-01-15 00:20 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.1, R 0.286 s 0.196
2023-01-15 00:20 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=1, R 0.532 s 0.026
2023-01-15 00:23 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.1, R 0.265 s 0.158
2023-01-14 23:33 R file-read snappy, parquet, table, nyctaxi_2010-01, R 0.567 s -0.271
2023-01-14 23:33 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.217 s 0.332
2023-01-14 23:34 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 0.816 s 0.323
2023-01-14 23:35 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 9.865 s -1.990
2023-01-14 23:37 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 16.766 s -1.427
2023-01-14 23:38 R file-write snappy, parquet, table, fanniemae_2016Q4, R 10.273 s -1.919
2023-01-14 23:40 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.967 s -1.269
2023-01-14 23:42 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 9.001 s 0.828
2023-01-14 23:42 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.493 s 0.074
2023-01-14 23:44 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 7.457 s 0.863
2023-01-14 23:48 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.733 s -1.050
2023-01-14 23:49 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.308 s 0.851
2023-01-14 23:50 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.473 s -0.896
2023-01-14 23:51 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.064 s 0.156
2023-01-14 23:51 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.568 s -0.410
2023-01-14 23:52 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.253 s -0.201
2023-01-14 23:53 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=1, R 0.276 s -0.160
2023-01-14 23:53 R tpch arrow, parquet, memory_map=False, TPCH-01, scale_factor=1, R 0.602 s -1.100
2023-01-14 23:53 R tpch arrow, native, memory_map=False, TPCH-01, scale_factor=10, R 1.008 s -0.424
2023-01-14 23:52 R partitioned-dataset-filter dims, dataset-taxi-parquet, R 0.604 s -0.439
2023-01-14 23:54 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=0.01, R 0.336 s -0.024
2023-01-14 23:55 R tpch arrow, parquet, memory_map=False, TPCH-03, scale_factor=0.1, R 0.306 s 0.119
2023-01-14 23:57 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=0.01, R 0.198 s 0.253
2023-01-14 23:57 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=1, R 0.330 s 0.251
2023-01-15 00:01 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=10, R 0.355 s 0.078
2023-01-15 00:06 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=10, R 3.798 s -0.559
2023-01-15 00:07 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=1, R 0.897 s -2.881
2023-01-15 00:10 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.01, R 0.211 s 0.111
2023-01-15 00:17 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=10, R 1.662 s -3.110
2023-01-15 00:18 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.01, R 0.209 s 0.210
2023-01-15 00:20 R tpch arrow, parquet, memory_map=False, TPCH-16, scale_factor=0.01, R 0.238 s 0.255
2023-01-15 00:21 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.1, R 0.322 s 0.188
2023-01-15 00:23 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=0.1, R 0.210 s 0.144
2023-01-15 00:23 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=1, R 0.542 s -0.291
2023-01-15 00:27 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.01, R 0.257 s 0.105
2023-01-15 00:29 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.01, R 0.453 s -0.071
2023-01-15 00:32 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=10, R 30.110 s -3.587
2023-01-15 00:34 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=1, R 0.228 s 0.134
2023-01-14 23:54 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=0.1, R 0.292 s -0.014
2023-01-14 23:55 R tpch arrow, parquet, memory_map=False, TPCH-02, scale_factor=10, R 1.072 s -1.248
2023-01-14 23:56 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=10, R 0.902 s -0.086
2023-01-14 23:59 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=10, R 0.640 s -0.521
2023-01-15 00:00 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=1, R 0.511 s 0.045
2023-01-15 00:05 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=10, R 0.616 s 0.008
2023-01-15 00:06 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.01, R 0.358 s -0.656
2023-01-15 00:07 R tpch arrow, parquet, memory_map=False, TPCH-09, scale_factor=0.1, R 0.469 s -2.859
2023-01-15 00:10 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=0.1, R 0.231 s 0.130
2023-01-15 00:11 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=1, R 0.543 s -0.141
2023-01-15 00:24 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=10, R 4.367 s -1.829
2023-01-15 00:29 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.1, R 0.734 s -0.752
2023-01-15 00:29 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=0.1, R 0.800 s -0.267
2023-01-15 00:34 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.1, R 0.204 s 0.178
2023-01-15 00:43 JavaScript vectorFromArray numbers 0.016 s 0.113
2023-01-15 00:44 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.187 s 0.914
2023-01-15 00:44 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s 0.079
2023-01-14 23:54 R tpch arrow, native, memory_map=False, TPCH-02, scale_factor=1, R 0.337 s -0.004
2023-01-14 23:58 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=10, R 1.208 s -0.389
2023-01-15 00:00 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=0.01, R 0.162 s 0.121
2023-01-15 00:02 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=1, R 0.663 s 0.007
2023-01-15 00:04 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.1, R 0.447 s -4.731
2023-01-15 00:07 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=1, R 0.487 s -3.708
2023-01-15 00:12 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.01, R 0.209 s 0.078
2023-01-15 00:13 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=0.01, R 0.184 s 0.078
2023-01-15 00:18 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=10, R 6.801 s -5.331
2023-01-15 00:18 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.1, R 0.286 s 0.134
2023-01-15 00:19 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=10, R 0.627 s -0.602
2023-01-15 00:21 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.01, R 0.217 s 0.194
2023-01-15 00:21 R tpch arrow, native, memory_map=False, TPCH-17, scale_factor=0.1, R 0.221 s 0.118
2023-01-15 00:22 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=10, R 6.997 s -0.851
2023-01-15 00:27 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=1, R 0.289 s 0.064
2023-01-15 00:29 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=0.01, R 0.398 s -0.580
2023-01-15 00:43 JavaScript vectorFromArray booleans 0.018 s 0.144
2023-01-14 23:55 R tpch arrow, native, memory_map=False, TPCH-03, scale_factor=0.1, R 0.233 s 0.151
2023-01-14 23:57 R tpch arrow, native, memory_map=False, TPCH-04, scale_factor=1, R 0.272 s 0.053
2023-01-14 23:58 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.1, R 0.266 s 0.179
2023-01-15 00:00 R tpch arrow, native, memory_map=False, TPCH-06, scale_factor=1, R 0.183 s 0.054
2023-01-15 00:01 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=10, R 3.268 s -0.314
2023-01-15 00:02 R tpch arrow, native, memory_map=False, TPCH-07, scale_factor=0.1, R 0.297 s 0.074
2023-01-15 00:04 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=0.1, R 0.572 s -4.252
2023-01-15 00:06 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.01, R 0.273 s 0.230
2023-01-15 00:11 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=1, R 0.331 s -0.062
2023-01-15 00:12 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=0.1, R 0.308 s -0.683
2023-01-15 00:15 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.01, R 0.217 s 0.055
2023-01-15 00:18 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=0.01, R 0.253 s 0.224
2023-01-15 00:20 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=1, R 0.326 s 0.103
2023-01-15 00:21 R tpch arrow, parquet, memory_map=False, TPCH-17, scale_factor=0.01, R 0.269 s 0.160
2023-01-15 00:24 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=10, R 3.485 s -1.395
2023-01-15 00:25 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=0.1, R 0.444 s -0.279
2023-01-15 00:26 R tpch arrow, native, memory_map=False, TPCH-19, scale_factor=10, R 5.687 s -4.168
2023-01-15 00:27 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=0.1, R 0.259 s 0.031
2023-01-15 00:27 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=1, R 0.965 s 0.058
2023-01-15 00:28 R tpch arrow, native, memory_map=False, TPCH-20, scale_factor=10, R 0.608 s -0.257
2023-01-14 23:57 R tpch arrow, parquet, memory_map=False, TPCH-04, scale_factor=0.1, R 0.244 s 0.182
2023-01-14 23:58 R tpch arrow, native, memory_map=False, TPCH-05, scale_factor=0.01, R 0.261 s 0.191
2023-01-15 00:00 R tpch arrow, parquet, memory_map=False, TPCH-06, scale_factor=0.01, R 0.203 s 0.165
2023-01-15 00:01 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=0.01, R 0.339 s 0.312
2023-01-15 00:09 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=0.1, R 0.336 s 0.205
2023-01-15 00:11 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.1, R 0.304 s 0.171
2023-01-15 00:13 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=10, R 2.695 s -15.169
2023-01-15 00:13 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=10, R 6.522 s -1.068
2023-01-15 00:14 R tpch arrow, parquet, memory_map=False, TPCH-13, scale_factor=0.1, R 0.431 s -0.410
2023-01-15 00:18 R tpch arrow, native, memory_map=False, TPCH-15, scale_factor=0.1, R 0.212 s 0.141
2023-01-15 00:20 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=10, R 0.893 s -0.411
2023-01-15 00:23 R tpch arrow, parquet, memory_map=False, TPCH-18, scale_factor=0.01, R 0.242 s 0.232
2023-01-15 00:25 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.1, R 0.445 s -0.004
2023-01-15 00:27 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.1, R 0.377 s 0.051
2023-01-15 00:29 R tpch arrow, native, memory_map=False, TPCH-21, scale_factor=1, R 2.909 s -2.469
2023-01-15 00:34 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=10, R 33.344 s -3.917
2023-01-15 00:35 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=1, R 0.459 s -0.086
2023-01-15 00:44 JavaScript toArray Vector numbers
2023-01-15 00:03 R tpch arrow, parquet, memory_map=False, TPCH-07, scale_factor=10, R 3.915 s -2.648
2023-01-15 00:03 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=0.01, R 0.394 s -2.737
2023-01-15 00:05 R tpch arrow, native, memory_map=False, TPCH-08, scale_factor=1, R 0.468 s -5.034
2023-01-15 00:05 R tpch arrow, parquet, memory_map=False, TPCH-08, scale_factor=1, R 0.854 s -3.887
2023-01-15 00:06 R tpch arrow, native, memory_map=False, TPCH-09, scale_factor=0.1, R 0.343 s -2.293
2023-01-15 00:09 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=1, R 0.654 s 0.034
2023-01-15 00:10 R tpch arrow, native, memory_map=False, TPCH-10, scale_factor=10, R 0.875 s 0.323
2023-01-15 00:10 R tpch arrow, parquet, memory_map=False, TPCH-10, scale_factor=10, R 3.736 s -0.169
2023-01-15 00:10 R tpch arrow, parquet, memory_map=False, TPCH-11, scale_factor=0.01, R 0.262 s 0.165
2023-01-15 00:11 R tpch arrow, native, memory_map=False, TPCH-11, scale_factor=10, R 0.872 s -0.438
2023-01-15 00:12 R tpch arrow, parquet, memory_map=False, TPCH-12, scale_factor=0.01, R 0.258 s 0.020
2023-01-15 00:12 R tpch arrow, native, memory_map=False, TPCH-12, scale_factor=1, R 0.492 s -2.459
2023-01-15 00:14 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=1, R 0.614 s -1.783
2023-01-15 00:15 R tpch arrow, native, memory_map=False, TPCH-13, scale_factor=10, R 3.454 s -9.329
2023-01-15 00:15 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=0.01, R 0.365 s -2.574
2023-01-15 00:16 R tpch arrow, native, memory_map=False, TPCH-14, scale_factor=0.1, R 0.337 s -5.304
2023-01-15 00:16 R tpch arrow, parquet, memory_map=False, TPCH-14, scale_factor=1, R 1.158 s -4.794
2023-01-15 00:19 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=1, R 0.591 s -0.063
2023-01-15 00:19 R tpch arrow, parquet, memory_map=False, TPCH-15, scale_factor=10, R 3.582 s -0.318
2023-01-15 00:20 R tpch arrow, native, memory_map=False, TPCH-16, scale_factor=0.1, R 0.223 s 0.144
2023-01-15 00:23 R tpch arrow, native, memory_map=False, TPCH-18, scale_factor=1, R 0.409 s -0.355
2023-01-15 00:30 R tpch arrow, parquet, memory_map=False, TPCH-21, scale_factor=1, R 3.197 s -4.241
2023-01-15 00:43 JavaScript vectorFromArray dictionary 0.016 s 0.805
2023-01-15 00:43 JavaScript Iterate Vector int64Array 0.004 s 0.154
2023-01-15 00:43 JavaScript Iterate Vector float64Array 0.002 s -0.411
2023-01-15 00:43 JavaScript Iterate Vector booleans 0.004 s 0.409
2023-01-15 00:44 JavaScript Iterate Vector string 0.125 s 1.045
2023-01-15 00:44 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s -1.123
2023-01-15 00:25 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=0.01, R 0.327 s 0.144
2023-01-15 00:27 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=0.01, R 0.322 s 0.053
2023-01-15 00:34 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=0.01, R 0.198 s 0.033
2023-01-15 00:43 JavaScript Iterate Vector uint64Array 0.004 s 0.164
2023-01-15 00:44 JavaScript Spread Vector string 0.146 s -0.079
2023-01-15 00:44 JavaScript toArray Vector uint16Array
2023-01-15 00:44 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.550
2023-01-15 00:44 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-15 00:25 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=1, R 1.344 s -0.658
2023-01-15 00:34 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.1, R 0.264 s 0.072
2023-01-15 00:43 JavaScript Iterate Vector numbers 0.002 s -0.390
2023-01-15 00:44 JavaScript Spread Vector float32Array 0.008 s -0.743
2023-01-15 00:44 JavaScript Spread Vector numbers 0.008 s 1.185
2023-01-15 00:44 JavaScript get Vector dictionary 0.002 s -1.298
2023-01-15 00:44 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.519
2023-01-15 00:44 JavaScript Table tracks, 1,000,000 0.096 s -1.449
2023-01-15 00:27 R tpch arrow, parquet, memory_map=False, TPCH-19, scale_factor=10, R 9.508 s -3.663
2023-01-15 00:43 JavaScript Iterate Vector uint32Array 0.002 s -1.040
2023-01-15 00:43 JavaScript Iterate Vector int8Array 0.002 s -0.407
2023-01-15 00:43 JavaScript Iterate Vector float32Array 0.002 s -1.266
2023-01-15 00:43 JavaScript Iterate Vector dictionary 0.004 s 0.423
2023-01-15 00:44 JavaScript Spread Vector dictionary 0.010 s 0.003
2023-01-15 00:28 R tpch arrow, parquet, memory_map=False, TPCH-20, scale_factor=10, R 6.201 s -0.753
2023-01-15 00:35 R tpch arrow, native, memory_map=False, TPCH-22, scale_factor=10, R 0.311 s -0.013
2023-01-15 00:43 JavaScript Iterate Vector int16Array 0.002 s -0.410
2023-01-15 00:44 JavaScript toArray Vector int64Array
2023-01-15 00:44 JavaScript toArray Vector booleans 0.010 s -1.321
2023-01-15 00:44 JavaScript get Vector uint64Array 0.003 s -0.128
2023-01-15 00:44 JavaScript get Vector float64Array 0.002 s 0.379
2023-01-15 00:34 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=0.01, R 0.250 s -0.105
2023-01-15 00:35 R tpch arrow, parquet, memory_map=False, TPCH-22, scale_factor=10, R 2.329 s -0.255
2023-01-15 00:43 JavaScript Iterate Vector int32Array 0.002 s 0.300
2023-01-15 00:44 JavaScript Spread Vector int32Array 0.007 s -0.012
2023-01-15 00:44 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.668
2023-01-15 00:44 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.833
2023-01-15 00:44 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.190 s -0.647
2023-01-15 00:44 JavaScript Table tracks, 1,000,000 0.050 s -0.290
2023-01-15 00:43 JavaScript Iterate Vector uint8Array 0.002 s -0.580
2023-01-15 00:44 JavaScript Spread Vector int8Array 0.006 s 0.049
2023-01-15 00:44 JavaScript toArray Vector uint32Array
2023-01-15 00:44 JavaScript toArray Vector int8Array
2023-01-15 00:44 JavaScript toArray Vector int32Array
2023-01-15 00:44 JavaScript toArray Vector float32Array
2023-01-15 00:43 JavaScript Iterate Vector uint16Array 0.002 s -0.706
2023-01-15 00:44 JavaScript Spread Vector int16Array 0.006 s 0.338
2023-01-15 00:44 JavaScript Spread Vector float64Array 0.008 s 1.522
2023-01-15 00:44 JavaScript Spread Vector booleans 0.010 s -1.893
2023-01-15 00:44 JavaScript toArray Vector int16Array
2023-01-15 00:44 JavaScript Table tracks, 1,000,000 0.249 s 1.064
2023-01-15 00:44 JavaScript Spread Vector uint8Array 0.007 s 0.037
2023-01-15 00:44 JavaScript Spread Vector uint32Array 0.007 s 0.687
2023-01-15 00:44 JavaScript toArray Vector uint8Array
2023-01-15 00:44 JavaScript get Vector float32Array 0.002 s 0.842
2023-01-15 00:44 JavaScript get Vector numbers 0.002 s -0.248
2023-01-15 00:44 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.697
2023-01-15 00:44 JavaScript Spread Vector uint16Array 0.006 s 0.015
2023-01-15 00:44 JavaScript Spread Vector uint64Array 0.012 s 0.007
2023-01-15 00:44 JavaScript Spread Vector int64Array 0.012 s -0.050
2023-01-15 00:44 JavaScript toArray Vector uint64Array
2023-01-15 00:44 JavaScript toArray Vector float64Array
2023-01-15 00:44 JavaScript toArray Vector string 0.143 s 1.099
2023-01-15 00:44 JavaScript get Vector uint16Array 0.003 s 0.036
2023-01-15 00:44 JavaScript toArray Vector dictionary 0.010 s -0.333
2023-01-15 00:44 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2023-01-15 00:44 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.106
2023-01-15 00:44 JavaScript Table 1,000,000, tracks 0.313 s -1.667
2023-01-15 00:44 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s -1.080
2023-01-15 00:44 JavaScript get Vector uint8Array 0.003 s 0.027
2023-01-15 00:44 JavaScript get Vector uint32Array 0.003 s 0.044
2023-01-15 00:44 JavaScript get Vector int8Array 0.003 s 0.059
2023-01-15 00:44 JavaScript get Vector int32Array 0.003 s -0.030
2023-01-15 00:44 JavaScript get Vector int16Array 0.003 s 0.010
2023-01-15 00:44 JavaScript get Vector booleans 0.002 s 0.609
2023-01-15 00:44 JavaScript get Vector int64Array 0.003 s 0.002
2023-01-15 00:44 JavaScript get Vector string 0.124 s 0.152
2023-01-15 00:44 JavaScript Parse write recordBatches, tracks 0.002 s -2.090
2023-01-15 00:44 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.380
2023-01-15 00:44 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s -1.168
2023-01-15 00:44 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.611
2023-01-15 00:44 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2023-01-15 00:44 JavaScript Parse read recordBatches, tracks 0.000 s 0.825
2023-01-15 00:44 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.372
2023-01-15 00:44 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s -1.046
2023-01-15 00:44 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2023-01-15 00:44 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.473
2023-01-15 00:44 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.000 s -0.555
2023-01-15 00:44 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s 0.245