Logs data stream

A logs data stream is a data stream type that stores log data more efficiently.

In benchmarks, log data stored in a logs data stream used ~2.5 times less disk space than a regular data stream. The exact impact varies by data set.

To create a logs data stream, set your template index.mode to logsdb:

resp = client.indices.put_index_template(
    name="my-index-template",
    index_patterns=[
        "logs-*"
    ],
    data_stream={},
    template={
        "settings": {
            "index.mode": "logsdb"
        }
    },
    priority=101,
)
print(resp)

const response = await client.indices.putIndexTemplate({
  name: "my-index-template",
  index_patterns: ["logs-*"],
  data_stream: {},
  template: {
    settings: {
      "index.mode": "logsdb",
    },
  },
  priority: 101,
});
console.log(response);

PUT _index_template/my-index-template
{
  "index_patterns": ["logs-*"],
  "data_stream": { },
  "template": {
     "settings": {
        "index.mode": "logsdb" 
     }
  },
  "priority": 101 
}

After the index template is created, new indices that use the template will be configured as a logs data stream. You can start indexing data and using the data stream.

You can also set the index mode and adjust other template settings in the Elastic UI.

If you have the required subscription, logsdb index mode uses synthetic _source, which omits storing the original _source field. Instead, the document source is synthesized from doc values or stored fields upon document retrieval.

If you don’t have the required subscription, logsdb mode uses the original _source field.

Before using synthetic source, make sure to review the restrictions.

When working with multi-value fields, the index.mapping.synthetic_source_keep setting controls how field values are preserved for synthetic source reconstruction. In logsdb, the default value is arrays, which retains both duplicate values and the order of entries. However, the exact structure of array elements and objects is not necessarily retained. Preserving duplicates and ordering can be critical for some log fields, such as DNS A records, HTTP headers, and log entries that represent sequential or repeated events.

In logsdb index mode, the following sort settings are applied by default:

You can override these default sort settings. For example, to sort on different fields and change the order, manually configure index.sort.field and index.sort.order. For more details, see Index Sorting.

When using the default sort settings, the host.name field is automatically injected into the index mappings as a keyword field to ensure that sorting can be applied. This guarantees that logs are efficiently sorted and retrieved based on the host.name and @timestamp fields.

To apply different sort settings to an existing data stream, update the data stream’s component templates, and then perform or wait for a rollover.

If you’re enabling logsdb index mode on a data stream that already exists, make sure to check mappings and sorting. The logsdb mode automatically maps host.name as a keyword if it’s included in the sort settings. If a host.name field already exists but has a different type, mapping errors might occur, preventing logsdb mode from being fully applied.

To avoid mapping conflicts, consider these options:

By default, logsdb index mode uses the best_compression codec, which applies ZSTD compression to stored fields. You can switch to the default codec for faster compression with a slightly larger storage footprint.

The logsdb index mode also automatically applies specialized codecs for numeric doc values, in order to optimize storage usage. Numeric fields are encoded using the following sequence of codecs:

Each encoding is evaluated according to heuristics determined by the data distribution. For example, the algorithm checks whether the data is monotonically non-decreasing or non-increasing. If so, delta encoding is applied; otherwise, the process continues with the next encoding method (offset).

Encoding is specific to each Lucene segment and is reapplied when segments are merged. The merged Lucene segment might use a different encoding than the original segments, depending on the characteristics of the merged data.

For keyword fields, Run Length Encoding (RLE) is applied to the ordinals, which represent positions in the Lucene segment-level keyword dictionary. This compression is used when multiple consecutive documents share the same keyword.

The logsdb index mode uses the following ignore settings. You can override these settings as needed.

By default, logsdb index mode sets ignore_malformed to true. With this setting, documents with malformed fields can be indexed without causing ingestion failures.

In logsdb index mode, the index.mapping.ignore_above setting is applied by default at the index level to ensure efficient storage and indexing of large keyword fields.The index-level default for ignore_above is 8191 characters. Using UTF-8 encoding, this results in a limit of 32764 bytes, depending on character encoding.

The mapping-level ignore_above setting takes precedence. If a specific field has an ignore_above value defined in its mapping, that value overrides the index-level index.mapping.ignore_above value. This default behavior helps to optimize indexing performance by preventing excessively large string values from being indexed.

If you need to customize the limit, you can override it at the mapping level or change the index level default.

In logsdb index mode, the setting index.mapping.total_fields.ignore_dynamic_beyond_limit is set to true by default. This setting allows dynamically mapped fields to be added on top of statically defined fields, even when the total number of fields exceeds the index.mapping.total_fields.limit. Instead of triggering an index failure, additional dynamically mapped fields are ignored so that ingestion can continue.

When the logsdb index mode uses synthetic _source and doc_values are disabled for a field in the mapping, Elasticsearch might set the store setting to true for that field. This ensures that the field’s data remains accessible for reconstructing the document’s source when using synthetic source.

For example, this adjustment occurs with text fields when store is false and no suitable multi-field is available for reconstructing the original value.

The logsdb index mode uses the following settings: