Top Outliers
Benchmarks
Date Lang Batch Benchmark Mean Z-Score Error
2022-11-17 04:19 Python csv-read uncompressed, arrow_table, file, fanniemae_2016Q4 1.256 s -0.486
2022-11-17 04:19 Python csv-read gzip, arrow_table, file, fanniemae_2016Q4 5.685 s -0.504
2022-11-17 04:21 Python csv-read gzip, arrow_table, file, nyctaxi_2010-01 8.426 s -0.220
2022-11-17 04:20 Python csv-read gzip, arrow_table, streaming, fanniemae_2016Q4 14.110 s 0.657
2022-11-17 04:24 Python dataframe-to-table type_floats 0.011 s 0.044
2022-11-17 04:21 Python csv-read uncompressed, arrow_table, file, nyctaxi_2010-01 1.129 s -0.051
2022-11-17 04:21 Python csv-read uncompressed, arrow_table, streaming, fanniemae_2016Q4 14.077 s 0.642
2022-11-17 04:22 Python csv-read uncompressed, arrow_table, streaming, nyctaxi_2010-01 11.882 s 0.086
2022-11-17 04:24 Python dataframe-to-table type_integers 0.010 s 0.643
2022-11-17 04:25 Python dataframe-to-table type_nested 2.927 s -1.557
2022-11-17 04:22 Python csv-read gzip, arrow_table, streaming, nyctaxi_2010-01 11.870 s 0.377
2022-11-17 04:24 Python dataframe-to-table type_strings 0.446 s 0.131
2022-11-17 04:24 Python dataframe-to-table chi_traffic_2020_Q1 20.450 s -0.880
2022-11-17 04:25 Python dataset-filter nyctaxi_2010-01 1.008 s -0.022
2022-11-17 04:24 Python dataframe-to-table type_dict 0.011 s 1.058
2022-11-17 04:30 Python dataset-read async=True, pre_buffer=true, nyctaxi_multi_parquet_s3 103.855 s -2.266
2022-11-17 04:35 Python dataset-read async=True, pre_buffer=false, nyctaxi_multi_parquet_s3 92.512 s -2.405
2022-11-17 04:49 Python dataset-selectivity 100%, chi_traffic_2020_Q1 1.221 s -4.475
2022-11-17 04:50 Python file-read lz4, feather, table, nyctaxi_2010-01 0.687 s 0.109
2022-11-17 04:49 Python dataset-selectivity 10%, chi_traffic_2020_Q1 1.199 s -0.067
2022-11-17 04:49 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.505 s -0.114
2022-11-17 04:49 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.655 s -0.733
2022-11-17 04:50 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 4.213 s 2.502
2022-11-17 04:50 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 0.967 s -0.147
2022-11-17 04:50 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 1.553 s 2.413
2022-11-17 04:51 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 1.331 s 1.558
2022-11-17 04:55 Python file-write uncompressed, feather, dataframe, fanniemae_2016Q4 13.680 s 0.346
2022-11-17 04:48 Python dataset-selectivity 10%, nyctaxi_multi_ipc_s3 2.044 s 0.188
2022-11-17 04:50 Python file-read snappy, parquet, table, nyctaxi_2010-01 0.922 s -0.025
2022-11-17 04:57 Python file-write snappy, parquet, table, nyctaxi_2010-01 7.515 s 0.930
2022-11-17 04:54 Python file-write snappy, parquet, dataframe, fanniemae_2016Q4 19.877 s 0.201
2022-11-17 04:48 Python dataset-selectivity 100%, nyctaxi_multi_parquet_s3 1.297 s 0.064
2022-11-17 04:48 Python dataset-read async=True, nyctaxi_multi_ipc_s3 258.830 s -2.127
2022-11-17 04:48 Python dataset-selectivity 10%, nyctaxi_multi_parquet_s3 1.246 s -0.257
2022-11-17 04:48 Python dataset-selectivity 1%, nyctaxi_multi_ipc_s3 2.037 s 0.208
2022-11-17 04:50 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 0.974 s -0.549
2022-11-17 04:50 Python file-read uncompressed, feather, table, nyctaxi_2010-01 0.942 s -1.078
2022-11-17 04:52 Python file-write uncompressed, parquet, dataframe, fanniemae_2016Q4 19.610 s 0.069
2022-11-17 04:48 Python dataset-select nyctaxi_multi_parquet_s3_repartitioned 1.567 s -1.727
2022-11-17 04:50 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 0.925 s -0.348
2022-11-17 04:50 Python file-read lz4, feather, table, fanniemae_2016Q4 0.831 s -0.778
2022-11-17 04:48 Python dataset-selectivity 1%, nyctaxi_multi_parquet_s3 1.178 s 0.237
2022-11-17 04:48 Python dataset-selectivity 1%, chi_traffic_2020_Q1 1.162 s -0.097
2022-11-17 04:57 Python file-write snappy, parquet, dataframe, nyctaxi_2010-01 9.004 s 0.864
2022-11-17 04:58 Python file-write lz4, feather, dataframe, nyctaxi_2010-01 3.005 s -2.538
2022-11-17 04:58 Python wide-dataframe use_legacy_dataset=false 0.506 s 0.737
2022-11-17 04:53 Python file-write snappy, parquet, table, fanniemae_2016Q4 10.361 s 0.310
2022-11-17 04:49 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 1.642 s -0.790
2022-11-17 04:55 Python file-write lz4, feather, dataframe, fanniemae_2016Q4 10.704 s 0.218
2022-11-17 04:48 Python dataset-selectivity 100%, nyctaxi_multi_ipc_s3 1.652 s 0.991
2022-11-17 04:58 Python wide-dataframe use_legacy_dataset=true 0.373 s 0.449
2022-11-17 05:13 JavaScript toArray Vector float64Array
2022-11-17 04:49 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 1.506 s 0.036
2022-11-17 04:50 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 5.614 s 2.855
2022-11-17 04:55 Python file-write lz4, feather, table, fanniemae_2016Q4 1.646 s -7.411
2022-11-17 04:56 Python file-write uncompressed, parquet, table, nyctaxi_2010-01 5.582 s 0.996
2022-11-17 04:57 Python file-write uncompressed, feather, dataframe, nyctaxi_2010-01 3.360 s 1.115
2022-11-17 04:49 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.322 s 0.650
2022-11-17 04:56 Python file-write uncompressed, parquet, dataframe, nyctaxi_2010-01 7.085 s 0.810
2022-11-17 04:51 Python file-write uncompressed, parquet, table, fanniemae_2016Q4 10.030 s 0.353
2022-11-17 04:54 Python file-write uncompressed, feather, table, fanniemae_2016Q4 5.366 s -2.543
2022-11-17 04:57 Python file-write lz4, feather, table, nyctaxi_2010-01 1.769 s -0.820
2022-11-17 05:13 JavaScript Spread Vector uint64Array 0.012 s 0.508
2022-11-17 05:13 JavaScript Iterate vectors lng, 1,000,000, Float32, tracks 0.023 s 0.888
2022-11-17 05:13 JavaScript Spread Vector uint16Array 0.007 s -0.213
2022-11-17 05:13 JavaScript toArray Vector int64Array
2022-11-17 05:13 JavaScript vectorFromArray dictionary 0.016 s 0.860
2022-11-17 05:13 JavaScript toArray Vector uint16Array
2022-11-17 05:13 JavaScript Slice toArray vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.929
2022-11-17 04:57 Python file-write uncompressed, feather, table, nyctaxi_2010-01 1.940 s 1.705
2022-11-17 05:13 JavaScript Iterate Vector uint64Array 0.004 s 0.665
2022-11-17 05:13 JavaScript Iterate Vector int16Array 0.002 s -1.075
2022-11-17 05:13 JavaScript vectorFromArray booleans 0.018 s -0.235
2022-11-17 05:13 JavaScript Iterate Vector int32Array 0.002 s -1.271
2022-11-17 05:13 JavaScript vectorFromArray numbers 0.016 s 0.557
2022-11-17 05:13 JavaScript Iterate Vector uint16Array 0.002 s -0.925
2022-11-17 05:13 JavaScript Iterate Vector int64Array 0.004 s 0.485
2022-11-17 05:13 JavaScript Iterate Vector uint32Array 0.002 s -0.185
2022-11-17 05:13 JavaScript Iterate Vector int8Array 0.002 s -0.831
2022-11-17 05:13 JavaScript Spread Vector int8Array 0.007 s -0.172
2022-11-17 05:13 JavaScript get Vector dictionary 0.002 s 0.050
2022-11-17 05:13 JavaScript Spread Vector float32Array 0.008 s 0.006
2022-11-17 05:13 JavaScript Spread Vector numbers 0.008 s -0.218
2022-11-17 05:13 JavaScript toArray Vector int8Array
2022-11-17 05:13 JavaScript toArray Vector int32Array
2022-11-17 05:13 JavaScript toArray Vector float32Array
2022-11-17 05:13 JavaScript toArray Vector numbers
2022-11-17 05:13 JavaScript Spread Vector dictionary 0.010 s 0.162
2022-11-17 05:13 JavaScript toArray Vector uint32Array
2022-11-17 05:13 JavaScript toArray Vector dictionary 0.010 s 0.371
2022-11-17 05:13 JavaScript get Vector uint8Array 0.003 s 0.647
2022-11-17 05:13 JavaScript get Vector uint32Array 0.003 s 0.403
2022-11-17 05:13 JavaScript Iterate Vector uint8Array 0.002 s -0.310
2022-11-17 05:13 JavaScript Iterate vectors lat, 1,000,000, Float32, tracks 0.023 s 0.884
2022-11-17 05:13 JavaScript Iterate vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 1.349
2022-11-17 05:13 JavaScript Slice toArray vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.530
2022-11-17 05:13 JavaScript Slice vectors lat, 1,000,000, Float32, tracks 0.000 s
2022-11-17 05:13 JavaScript Iterate Vector float32Array 0.002 s -2.339
2022-11-17 05:13 JavaScript Spread Vector uint8Array 0.007 s -0.172
2022-11-17 05:13 JavaScript Iterate Vector float64Array 0.002 s -1.150
2022-11-17 05:13 JavaScript Iterate Vector booleans 0.004 s 0.722
2022-11-17 05:13 JavaScript Iterate Vector string 0.126 s 0.024
2022-11-17 05:13 JavaScript Spread Vector int64Array 0.012 s 0.489
2022-11-17 05:13 JavaScript Spread Vector float64Array 0.008 s -0.260
2022-11-17 05:13 JavaScript Iterate Vector numbers 0.002 s -1.131
2022-11-17 05:13 JavaScript Iterate Vector dictionary 0.004 s 1.217
2022-11-17 05:13 JavaScript Spread Vector uint32Array 0.007 s -0.078
2022-11-17 05:13 JavaScript Spread Vector int32Array 0.007 s -0.101
2022-11-17 05:13 JavaScript toArray Vector uint8Array
2022-11-17 05:13 JavaScript Spread Vector int16Array 0.007 s -0.345
2022-11-17 05:13 JavaScript toArray Vector uint64Array
2022-11-17 05:13 JavaScript toArray Vector string 0.145 s 0.484
2022-11-17 05:13 JavaScript get Vector int16Array 0.003 s 0.583
2022-11-17 05:13 JavaScript Spread Vector booleans 0.010 s 0.796
2022-11-17 05:13 JavaScript Spread Vector string 0.146 s -0.001
2022-11-17 05:13 JavaScript toArray Vector int16Array
2022-11-17 05:13 JavaScript get Vector int64Array 0.003 s -0.223
2022-11-17 05:13 JavaScript get Vector booleans 0.002 s 0.011
2022-11-17 05:13 JavaScript get Vector string 0.124 s 0.045
2022-11-17 05:13 JavaScript toArray Vector booleans 0.010 s 0.724
2022-11-17 05:13 JavaScript get Vector uint16Array 0.003 s 0.506
2022-11-17 05:13 JavaScript get Vector uint64Array 0.003 s -0.906
2022-11-17 05:13 JavaScript Get values by index lng, 1,000,000, Float32, tracks 0.030 s 0.549
2022-11-17 05:13 JavaScript Get values by index destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.642
2022-11-17 05:13 JavaScript Iterate vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 1.317
2022-11-17 05:13 JavaScript Table tracks, 1,000,000 0.050 s 0.174
2022-11-17 05:13 JavaScript get Vector int8Array 0.003 s -0.294
2022-11-17 05:13 JavaScript get Vector float32Array 0.002 s -0.356
2022-11-17 05:13 JavaScript Slice vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2022-11-17 05:13 JavaScript Spread vectors lat, 1,000,000, Float32, tracks 0.184 s 1.334
2022-11-17 05:13 JavaScript Spread vectors origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.107 s 0.574
2022-11-17 05:13 JavaScript Table 1,000,000, tracks 0.272 s -0.012
2022-11-17 05:13 JavaScript Table Direct Count lat, 1,000,000, gt, Float32, 0, tracks 0.032 s -0.337
2022-11-17 05:13 JavaScript get Vector int32Array 0.003 s -0.289
2022-11-17 05:13 JavaScript get Vector numbers 0.002 s 3.003
2022-11-17 05:13 JavaScript Parse read recordBatches, tracks 0.000 s 0.120
2022-11-17 05:13 JavaScript Get values by index lat, 1,000,000, Float32, tracks 0.030 s 0.274
2022-11-17 05:13 JavaScript Get values by index origin, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.039 s 0.555
2022-11-17 05:13 JavaScript Slice toArray vectors lat, 1,000,000, Float32, tracks 0.000 s -0.126
2022-11-17 05:13 JavaScript get Vector float64Array 0.002 s 3.328
2022-11-17 05:13 JavaScript Parse write recordBatches, tracks 0.002 s -0.239
2022-11-17 05:13 JavaScript Table Direct Count lng, 1,000,000, gt, Float32, 0, tracks 0.032 s -0.805
2022-11-17 05:13 JavaScript Slice toArray vectors lng, 1,000,000, Float32, tracks 0.001 s -1.199
2022-11-17 05:13 JavaScript Slice vectors lng, 1,000,000, Float32, tracks 0.000 s
2022-11-17 05:13 JavaScript Table tracks, 1,000,000 0.096 s -1.942
2022-11-17 05:13 JavaScript Slice vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.000 s
2022-11-17 05:13 JavaScript Spread vectors lng, 1,000,000, Float32, tracks 0.193 s -1.451
2022-11-17 05:13 JavaScript Spread vectors destination, 1,000,000, Dictionary<Int8, Utf8>, tracks 0.108 s -0.178
2022-11-17 05:13 JavaScript Table tracks, 1,000,000 0.318 s -2.220
2022-11-17 05:13 JavaScript Table Direct Count origin, 1,000,000, eq, Dictionary<Int8, Utf8>, Seattle, tracks 0.032 s 0.118