Bloom filter

This page describes configuring the Bloom filter for Apache Pinot

When a column is configured to use this filter, Pinot creates one Bloom filter per segment. The Bloom filter help to prune segments that do not contain any record matching an EQUALITY or IN predicate.

Note: Support for IN clause is limited to <= 10 values in the predicate, this is to ensure pruning overhead is minimal.

This is useful for query patterns like below where Bloom Filter is defined on playerID column in the table:

SELECT COUNT(*) 
FROM baseballStats 
WHERE playerID = 12345

OR

SELECT COUNT(*) 
FROM baseballStats 
WHERE playerID IN(12345, 45668, 56789)

Details

A Bloom filter is a probabilistic data structure used to definitively determine if an element is not present in a dataset, but it cannot be employed to determine if an element is present in the dataset. This limitation arises because Bloom filters may produce false positives but never yield false negatives.

An intriguing aspect of these filters is the existence of a mathematical formula that establishes a relationship between their size, the cardinality of the dataset they index, and the rate of false positives.

In Pinot, this cardinality corresponds to the number of unique values expected within each segment. If necessary, the false positive rate and the index size can be configured.

Configuration

Bloom filters are deactivated by default, implying that columns will not be indexed unless they are explicitly configured within the table configuration.

There are 3 optional parameters to configure the Bloom filter:

Parameter	Default	Description
fpp	0.05	False positive probability of the Bloom filter (from 0 to 1).
maxSizeInBytes	0 (unlimited)	Maximum size of the Bloom filter.
loadOnHeap	false	Whether to load the Bloom filter using heap memory or off-heap memory.

The lower the fpp (false positive probability), the greater the accuracy of the Bloom filter, but this reduction in fpp will also lead to an increase in the index size. It's important to note that maxSizeInBytes takes precedence over fpp. If maxSizeInBytes is set to a value greater than 0 and the calculated size of the Bloom filter, based on the specified fpp, exceeds this size limit, Pinot will adjust the fpp to ensure that the Bloom filter size remains within the specified limit.

Similar to other indexes, a Bloom filter can be explicitly deactivated by setting the special parameter disabled to true.

Example

For example the following table config enables the Bloom filter in the playerId column using the default values:

Configured in tableConfig fieldConfigList

{
  "tableName": "somePinotTable",
  "fieldConfigList": [
    {
      "name": "playerID",
      "encodingType": "RAW",
      "indexes": {
        "bloom": {}
      }
    },
    ...
  ],
  ...
}

In case some parameter needs to be customized, they can be included in fieldConfigList.indexes.bloom. Remember that even the example customizes all parameters, you can just modify the ones you need.

Configured in tableConfig fieldConfigList

{
  "tableName": "somePinotTable",
  "fieldConfigList": [
    {
      "name": "playerID",
      "encodingType": "RAW",
      "indexes": {
        "bloom": {
          "fpp": 0.01,
          "maxSizeInBytes": 1000000,
          "loadOnHeap": true
        }
      }
    },
    ...
  ],
  ...
}

Older configuration

Use default settings

To use default values, include the name of the column in tableIndexConfig.bloomFilterColumns.

For example:

Part of a tableConfig

{
  "tableName": "somePinotTable",
  "tableIndexConfig": {
    "bloomFilterColumns": [
      "playerID",
      ...
    ],
    ...
  },
  ...
}

Customized parameters

To specify custom parameters, add a new entry in tableIndexConfig.bloomFilterConfig object. The key should be the name of the column and the value should be an object similar to the one that can be used in the Bloom section of fieldConfigList.

For example:

Part of a tableConfig

{
  "tableIndexConfig": {
    "bloomFilterConfigs": {
      "playerID": {
        "fpp": 0.01,
        "maxSizeInBytes": 1000000,
        "loadOnHeap": true
      },
      ...
    },
    ...
  },
  ...
}