Query #

Data Skipping By Order #

Paimon by default records the maximum and minimum values of each field in the manifest file.

In the query, according to the WHERE condition of the query, according to the statistics in the manifest do files filtering, if the filtering effect is good, the query would have been minutes of the query will be accelerated to milliseconds to complete the execution.

Often the data distribution is not always effective filtering, so if we can sort the data by the field in WHERE condition? You can take a look to Flink COMPACT Action or Flink COMPACT Procedure or Spark COMPACT Procedure.

Data Skipping By File Index #

You can use file index too, it filters files by index on the read side.

CREATE TABLE <PAIMON_TABLE> (<COLUMN> <COLUMN_TYPE> , ...) WITH (
    'file-index.bloom-filter.columns' = 'c1,c2',
    'file-index.bloom-filter.c1.items' = '200'
);

Define file-index.bloom-filter.columns, Paimon will create its corresponding index file for each file. If the index file is too small, it will be stored directly in the manifest, or in the directory of the data file. Each data file corresponds to an index file, which has a separate file definition and can contain different types of indexes with multiple columns.

Data file index is an external index file corresponding to a certain data file. If the index file is too small, it will be stored directly in the manifest, otherwise in the directory of the data file. Each data file corresponds to an index file, which has a separate file definition and can contain different types of indexes with multiple columns.

Different file index may be efficient in different scenario. For example bloom filter may speed up query in point lookup scenario. Using a bitmap may consume more space but can result in greater accuracy.

Currently, file index is only supported in append-only table.

Bloom Filter:

file-index.bloom-filter.columns: specify the columns that need bloom filter index.
file-index.bloom-filter.<column_name>.fpp to config false positive probability.
file-index.bloom-filter.<column_name>.items to config the expected distinct items in one data file.

Bitmap:

file-index.bitmap.columns: specify the columns that need bitmap index.

More filter types will be supported…

If you want to add file index to existing table, without any rewrite, you can use rewrite_file_index procedure. Before we use the procedure, you should config appropriate configurations in target table. You can use ALTER clause to config file-index.<filter-type>.columns to the table.

How to invoke: see flink procedures