Benchmarks
Date Language Batch Benchmark Mean Z-Score
2021-10-12 19:28 R file-read snappy, parquet, table, fanniemae_2016Q4, R 1.215 s 0.612351
2021-10-12 19:28 R file-read snappy, parquet, dataframe, fanniemae_2016Q4, R 1.444 s 0.912159
2021-10-12 19:30 R file-read uncompressed, feather, table, nyctaxi_2010-01, R 0.217 s -1.604974
2021-10-12 19:32 R file-write uncompressed, parquet, table, fanniemae_2016Q4, R 7.835 s 0.546521
2021-10-12 19:38 R file-write uncompressed, feather, dataframe, fanniemae_2016Q4, R 6.600 s -1.786162
2021-10-12 19:40 R file-write uncompressed, parquet, table, nyctaxi_2010-01, R 4.896 s -0.491961
2021-10-12 19:47 R partitioned-dataset-filter payment_type_3, dataset-taxi-parquet, R 1.789 s 2.306810
2021-10-12 19:51 R tpch arrow, parquet, memory_map=False, query_id=6, scale_factor=10, R 1.142 s 2.277709
2021-10-12 19:51 R tpch arrow, feather, memory_map=False, query_id=6, scale_factor=10, R 2.483 s 2.019742
2021-10-12 19:31 R file-read lz4, feather, table, nyctaxi_2010-01, R 0.697 s -0.054175
2021-10-12 19:48 R tpch arrow, parquet, memory_map=False, query_id=1, scale_factor=1, R 0.592 s 1.060515
2021-10-12 19:30 R file-read snappy, parquet, dataframe, nyctaxi_2010-01, R 1.221 s 0.907625
2021-10-12 19:48 R tpch arrow, feather, memory_map=False, query_id=1, scale_factor=1, R 0.533 s -1.467703
2021-10-12 19:29 R file-read lz4, feather, table, fanniemae_2016Q4, R 0.558 s 0.838917
2021-10-12 19:35 R file-write snappy, parquet, table, fanniemae_2016Q4, R 8.289 s 0.528516
2021-10-12 19:49 R tpch arrow, parquet, memory_map=False, query_id=1, scale_factor=10, R 2.866 s 1.704124
2021-10-12 19:50 R tpch arrow, native, memory_map=False, query_id=6, scale_factor=10, R 0.205 s 0.490141
2021-10-12 19:21 R dataframe-to-table type_floats, R 0.013 s 0.953832
2021-10-12 19:42 R file-write snappy, parquet, table, nyctaxi_2010-01, R 6.535 s -0.587276
2021-10-12 19:49 R tpch arrow, feather, memory_map=False, query_id=1, scale_factor=10, R 2.649 s -0.809571
2021-10-12 19:29 R file-read lz4, feather, dataframe, fanniemae_2016Q4, R 8.381 s 0.471615
2021-10-12 19:32 R file-read lz4, feather, dataframe, nyctaxi_2010-01, R 13.530 s 0.092530
2021-10-12 19:39 R file-write lz4, feather, dataframe, fanniemae_2016Q4, R 5.241 s -2.336472
2021-10-12 19:21 R dataframe-to-table chi_traffic_2020_Q1, R 3.405 s 0.265438
2021-10-12 19:28 R file-read uncompressed, feather, table, fanniemae_2016Q4, R 0.320 s -1.639368
2021-10-12 19:29 R file-read uncompressed, feather, dataframe, fanniemae_2016Q4, R 10.044 s -1.229266
2021-10-12 19:34 R file-write uncompressed, parquet, dataframe, fanniemae_2016Q4, R 12.327 s -0.050751
2021-10-12 19:47 R partitioned-dataset-filter vignette, dataset-taxi-parquet, R 0.560 s 3.101986
2021-10-12 19:21 R dataframe-to-table type_strings, R 0.489 s 0.231143
2021-10-12 19:30 R file-read uncompressed, parquet, dataframe, nyctaxi_2010-01, R 1.160 s 0.915863
2021-10-12 19:36 R file-write snappy, parquet, dataframe, fanniemae_2016Q4, R 12.751 s 0.221975
2021-10-12 19:48 R tpch arrow, native, memory_map=False, query_id=1, scale_factor=1, R 0.185 s -0.027035
2021-10-12 19:50 R tpch arrow, parquet, memory_map=False, query_id=6, scale_factor=1, R 0.355 s 1.825546
2021-10-12 19:30 R file-read snappy, parquet, table, nyctaxi_2010-01, R 1.106 s 1.083028
2021-10-12 19:37 R file-write uncompressed, feather, table, fanniemae_2016Q4, R 2.821 s 0.458585
2021-10-12 19:44 R file-write snappy, parquet, dataframe, nyctaxi_2010-01, R 7.741 s -0.995611
2021-10-12 19:31 R file-read uncompressed, feather, dataframe, nyctaxi_2010-01, R 13.965 s 0.410605
2021-10-12 19:44 R file-write uncompressed, feather, table, nyctaxi_2010-01, R 1.275 s 1.029339
2021-10-12 19:21 R dataframe-to-table type_integers, R 0.010 s 0.943222
2021-10-12 19:46 R file-write lz4, feather, table, nyctaxi_2010-01, R 1.473 s 1.086697
2021-10-12 19:47 R partitioned-dataset-filter small_no_files, dataset-taxi-parquet, R 0.587 s -1.932645
2021-10-12 19:49 R tpch arrow, native, memory_map=False, query_id=6, scale_factor=1, R 0.110 s 0.187878
2021-10-12 19:21 R dataframe-to-table type_dict, R 0.052 s -0.084232
2021-10-12 19:27 R dataframe-to-table type_simple_features, R 3.386 s 0.797995
2021-10-12 19:28 R file-read uncompressed, parquet, dataframe, fanniemae_2016Q4, R 1.458 s 0.931365
2021-10-12 19:29 R file-read uncompressed, parquet, table, nyctaxi_2010-01, R 1.051 s 0.401625
2021-10-12 19:45 R file-write uncompressed, feather, dataframe, nyctaxi_2010-01, R 2.257 s -1.783899
2021-10-12 19:47 R file-write lz4, feather, dataframe, nyctaxi_2010-01, R 2.184 s -1.450773
2021-10-12 19:47 R partitioned-dataset-filter count_rows, dataset-taxi-parquet, R 0.088 s 1.007710
2021-10-12 19:48 R tpch arrow, native, memory_map=False, query_id=1, scale_factor=10, R 0.618 s -0.472925
2021-10-12 19:21 R dataframe-to-table type_nested, R 0.528 s 0.234378
2021-10-12 19:27 R file-read uncompressed, parquet, table, fanniemae_2016Q4, R 1.212 s 0.410336
2021-10-12 19:41 R file-write uncompressed, parquet, dataframe, nyctaxi_2010-01, R 5.873 s -0.818077
2021-10-12 19:50 R tpch arrow, feather, memory_map=False, query_id=6, scale_factor=1, R 0.495 s -2.299807
2021-10-12 19:38 R file-write lz4, feather, table, fanniemae_2016Q4, R 1.382 s 1.708601