Benchmarks
Date Language Batch Benchmark Mean Z-Score
2021-10-06 07:59 Python file-read uncompressed, feather, table, fanniemae_2016Q4 2.294 s -0.486838
2021-10-06 08:01 Python file-read lz4, feather, table, nyctaxi_2010-01 0.681 s -2.646519
2021-10-06 08:00 Python file-read uncompressed, parquet, dataframe, nyctaxi_2010-01 7.853 s 0.702024
2021-10-06 08:01 Python file-read uncompressed, feather, dataframe, nyctaxi_2010-01 8.030 s 0.533496
2021-10-06 08:00 Python file-read snappy, parquet, table, nyctaxi_2010-01 1.016 s 1.317537
2021-10-06 07:58 Python file-read uncompressed, parquet, dataframe, fanniemae_2016Q4 3.711 s 0.850224
2021-10-06 07:59 Python file-read uncompressed, feather, dataframe, fanniemae_2016Q4 4.821 s 0.248664
2021-10-06 08:01 Python file-read lz4, feather, dataframe, nyctaxi_2010-01 7.556 s 0.421005
2021-10-06 07:58 Python file-read uncompressed, parquet, table, fanniemae_2016Q4 1.257 s 1.309025
2021-10-06 07:59 Python file-read uncompressed, parquet, table, nyctaxi_2010-01 1.017 s 1.040061
2021-10-06 07:58 Python file-read snappy, parquet, table, fanniemae_2016Q4 1.117 s 1.123499
2021-10-06 08:00 Python file-read uncompressed, feather, table, nyctaxi_2010-01 1.174 s 0.452336
2021-10-06 07:58 Python file-read snappy, parquet, dataframe, fanniemae_2016Q4 3.616 s 1.284457
2021-10-06 08:00 Python file-read snappy, parquet, dataframe, nyctaxi_2010-01 7.834 s 0.775306
2021-10-06 07:59 Python file-read lz4, feather, dataframe, fanniemae_2016Q4 3.124 s 0.331734
2021-10-06 07:59 Python file-read lz4, feather, table, fanniemae_2016Q4 0.611 s -1.506391