Version: v0.3.1

Index configuration

This page describes how to configure an index.

In addition to the index_id, the index configuration lets you define five items:

The index-uri: it defines where the index files should be stored.
The doc mapping: it defines how a document and the fields it contains are stored and indexed for a given index.
The indexing settings: it defines the timestamp field used for sharding, and some more advanced parameters like the merge policy.
The search settings: it defines the default search fields default_search_fields, a list of fields that Quickwit will search into if the user query does not explicitly target a field.
The (data) sources: it defines a list of sources of types like file or Kafka source.

Configuration is set at index creation and cannot be modified except for the sources using the CLI quickwit source commands.

Config file format

The index configuration format is YAML. When a key is absent from the configuration file, the default value is used. Here is a complete example suited for the HDFS logs dataset:

version: 0 # File format version.

index_id: "hdfs"

index_uri: "s3://my-bucket/hdfs"

doc_mapping:
  mode: lenient
  field_mappings:
    - name: timestamp
      type: i64
      fast: true
    - name: severity_text
      type: text
      tokenizer: raw
    - name: body
      type: text
      tokenizer: default
      record: position
    - name: resource
      type: object
      field_mappings:
        - name: service
          type: text
          tokenizer: raw
  tag_fields: ["resource.service"]

indexing_settings:
  timestamp_field: timestamp

search_settings:
  default_search_fields: [severity_text, body]

sources:
 - hdfs: hdfs-log-kafka
   source_type: kafka
   params:
     topic: hdfs-logs
     client_params:
       bootstrap.servers: localhost:9092
       group.id: quickwit-consumer-group
       security.protocol: SSL

Index uri

The index-uri defines where the index files (also called splits) should be stored. This parameter expects a storage uri.

The index-uri parameter is optional. By default, the index-uri will be computed by concatenating the index-id with the default_index_root_uri defined in the Quickwit's config.

caution

The file storage will not work when running quickwit in distributed mode. Today, only the s3 storage is available when running several searcher nodes.

Doc mapping

The doc mapping defines how a document and the fields it contains are stored and indexed for a given index. A document is a collection of named fields, each having its own data type (text, binary, i64, u64, f64).

Variable	Description	Default value
`field_mappings`	Collection of field mapping, each having its own data type (text, binary, i64, u64, f64).	[]
`mode`	Defines how quickwit should handle document fields that are not present in the `field_mappings`. In particular, the "dynamic" mode makes it possible to use quickwit in a schemaless manner. (See mode)	`lenient`
`dynamic_mapping`	This parameter is only allowed when `mode` is set to `dynamic`. It then defines whether dynamically mapped fields should be indexed, stored, etc.	(See mode)
`tag_fields`	Collection of fields already defined in `field_mappings` whose values will be stored in a dedicated `tags` (1)	[]
`store_source`	Whether or not the original JSON document is stored or not in the index.	false

(1) Learn more on the tags usage.

Field types

Each field has a type that indicates the kind of data it contains, such as integer on 64 bits or text. Quickwit supports the following raw types text, i64, u64, f64, and bytes, and also supports composite types such as array and object. Behind the scenes, Quickwit is using tantivy field types, don't hesitate to look at tantivy documentation if you want to go into the details.

Raw types

text type

This field is a text field that will be analyzed and split into tokens before indexing. This kind of field is tailored for full-text search.

Example of a mapping for a text field:

name: body
description: Body of the document
type: text
tokenizer: default
record: position

Parameters for text field

Variable	Description	Default value
`description`	Optional description for the field.	`None`
`stored`	Whether value is stored in the document store	`true`
`tokenizer`	Name of the `Tokenizer`, choices between `raw`, `default` and `en_stem`	`default`
`record`	Describes the amount of information indexed, choices between `basic`, `freq` and `position`	`basic`
`fast`	Whether value is stored in a fast field. The fast field will contain the term ids. The effective cardinality depends on the tokenizer. When creating fast fields on text fields it is recommended to use the "raw" tokenizer, since it will store the original text unchanged. The "default" tokenizer will store the terms as lower case and this will be reflected in the dictionary (see tokenizers).	`false`

Description of available tokenizers

Tokenizer	Description
`raw`	Does not process nor tokenize text
`default`	Chops the text on according to whitespace and punctuation, removes tokens that are too long, and converts to lowercase
`en_stem`	Like `default`, but also applies stemming on the resulting tokens

Description of record options

Record option	Description
`basic`	Records only the `DocId`s
`freq`	Records the document ids as well as the term frequency
`position`	Records the document id, the term frequency and the positions of occurrences.

Indexing with position is required to run phrase queries.

Numeric types: `i64`, `u64` and `f64` type

Quickwit handles three numeric types: i64, u64, and f64.

Numeric values can be stored in a fast field (the equivalent of Lucene's DocValues) which is a column-oriented storage.

Example of a mapping for an i64 field:

name: timestamp
descripton: UNIX timestamp of the document creation date
type: i64
stored: true
indexed: true
fast: true

Parameters for i64, u64 and f64 field

Variable	Description	Default value
`description`	Optional description for the field.	`None`
`stored`	Whether value is stored in the document store	`true`
`indexed`	Whether value is indexed	`true`
`fast`	Whether value is stored in a fast field	`false`

`bytes` type

The bytes type accepts a binary value as a Base64 encoded string.

Example of a mapping for a bytes field:

name: binary
type: bytes
stored: true
indexed: true
fast: true

Parameters for bytes field

Variable	Description	Default value
`description`	Optional description for the field.	`None`
`stored`	Whether value is stored in the document store	`true`
`indexed`	Whether value is indexed	`true`
`fast`	Whether value is stored in a fast field. Only on 1:1 cardinality, not supported on `array<bytes>` fields	`false`

`json` type

The json type accepts a JSON object.

Example of a mapping for a JSON field:

name: parameters
type: json
stored: true
indexed: true
tokenizer: "default"

Parameters for JSON field

Variable	Description	Default value
`description`	Optional description for the field.	`None`
`stored`	Whether value is stored in the document store	`true`
`indexed`	Whether value is indexed	`true`
`tokenizer`	Only affects strings in the json object. Name of the `Tokenizer`, choices between `raw`, `default` and `en_stem`	`default`
`record`	Only affects strings in the json object. Describes the amount of information indexed, choices between `basic`, `freq` and `position`	`basic`

Note that the tokenizer and the record have the same definition and the same effect as for the text field.

To search into a json object, one then needs to extend the field name with the path that will lead to the target value.

For instance, when indexing the following object:

{
    "product_name": "droopy t-shirt",
    "attributes": {
        "color": ["red", "green", "white"],
        "size:": "L"
    }
}

Assuming attributes as been defined as a field mapping as follows:

- type: json
  name: attributes

attributes.color:red is then a valid query.

If, in addition, attributes is set as a default search field, then color:red is a valid query.

Composite types

array

Quickwit supports arrays for all raw types except for object types.

To declare an array type of i64 in the index config, you just have to set the type to array<i64>.

object

Quickwit supports nested objects as long as it does not contain arrays of objects.

name: resource
type: object
field_mappings:
  - name: service
    type: text

Mode

The mode describes how Quickwit should behave when it receives a field that is not defined in the field mapping.

Quickwit offers you three different modes:

lenient: unmapped fields are dismissed by Quickwit.
strict: if a document contains a field that is not mapped, quickwit will dismiss it, and count it as an error.
dynamic: unmapped fields are gathered by Quickwit and handled as defined in the dynamic_mapping parameter.

dynamic_mapping offers the same configuration options as when configuring a json field. It defaults to:

- indexed: true
- stored: true
- tokenizer: raw
- record: basic

The dynamic mode makes it possible to operate Quickwit in a schemaless manner, or with a partial schema.

If the dynamic_mapping has been set as indexed (this is the default), fields that were mapped thanks to the dynamic mode can be searched, by targeting the path required to reach them from the root of the json object.

For instance, in a entirely schemaless settings, a minimal index configuration could be:

version: 0
index_id: my-dynamic-index
# note we did not map anything.
doc_mapping:
  mode: dynamic

We could then index a complex document like the following:

{
  "endpoint": "/admin",
  "query_params": {
    "ctk": "e42bb897d",
    "page": "eeb"
  },
  "src": {
    "ip": "8.8.8.8",
    "port": 53,
  },
  //...
}

The following queries are then valid, and match the document above.

// Fields can be searched simply.
endpoint:/admin

// Nested object can be queried by specifying a `.` separated
// path from the root of the json object to the given field.
query_params.ctk:e42bb897d

// numbers are searchable too
src.port:53

// and of course we can combine them with boolean operators.
src.port:53 AND query_params.ctk:e42bb897d

Field name validation rules

Currently Quickwit only accepts field name that matches the following regular expression: [a-zA-Z][_\.\-a-zA-Z0-9]*$

In plain language:

it needs to have at least one character.
it should only contain latin letter [a-zA-Z] digits [0-9] or (., -, _).
the first character needs to be a letter.

caution

For field names containing the . character, you will need to escape it when referencing them. Otherwise the . character will be interpreted as a JSON object property access. Because of this, it is recommended to avoid using field names containing the . character.

Behavior with fields not defined in the config

Fields in your JSON document that are not defined in the index config will be ignored.

Behavior with null values or missing fields

Fields with null or missing fields in your JSON document will be silently ignored when indexing.

Indexing settings

This section describes indexing settings for a given index.

Variable	Description	Default value
`timestamp_field`	Timestamp field used for sharding documents in splits (1).	None
`commit_timeout_secs`	Maximum number of seconds before committing a split since its creation.	60
`split_num_docs_target`	Maximum number of documents in a split. Note that this is not a hard limit.	10_000_000
`merge_policy.merge_factor`	Number of splits to merge.	10
`merge_policy.max_merge_factor`	Maximum number of splits to merge.	12
`resources.num_threads`	Number of threads per source.	1
`resources.heap_size`	Indexer heap size per source per index.	2_000_000_000

(1) Learn more on time sharding

Indexer memory usage

Indexer works with a default heap of 2 GiB of memory. This does not directly reflect the overall memory usage, but doubling this value should give a fair approximation.

Search settings

This section describes search settings for a given index.

Variable	Description	Default value
`search_default_fields`	Default list of fields that will be used for search.	None

Sources

An index can have one or several data sources. Learn how to configure them.

Config file format​

Index uri​

caution

Doc mapping​

Field types​

Raw types​

text type​

Description of available tokenizers​

Numeric types: i64, u64 and f64 type​

bytes type​

json type​

Composite types​

array​

object​

Mode​

Field name validation rules​

caution

Behavior with fields not defined in the config​

Behavior with null values or missing fields​

Indexing settings​

Indexer memory usage​

Search settings​

Sources​

Config file format

Index uri

Doc mapping

Field types

Raw types

text type

Description of available tokenizers

Numeric types: `i64`, `u64` and `f64` type

`bytes` type

`json` type

Composite types

array

object

Mode

Field name validation rules

Behavior with fields not defined in the config

Behavior with null values or missing fields

Indexing settings

Indexer memory usage

Search settings

Sources