Indexing and Search Guide

Koverse features a unique indexing and search capability. Unlike some open source options like Elastic Search and Solr, Koverse is capable of storing original records and index entries in the same system, eliminating the need for inefficient integration code between an indexing system like Elastic Search and a record storage system like HBase. Koverse stores original records and index entries and schema information in the same Accumulo instance and therefore can provide unparalleled efficiency, security, and performance.

This guide details search syntax and guidance for how to configure indexing to support specific searches.

Search Languages

Koverse supports several search languages for fetching subsets of records using Koverse’s indexes. Each language is designed to make it easy to express search criteria in various contexts.

Below we describe the various types of search language syntax in detail.

Lucene Search Syntax


Koverse supports a popular subset of Lucene for searching data sets via the Koverse user interface, or for web applications that allow end users to enter their own search criteria. The syntax allows for rich searching by using Boolean logic, term grouping, ranges, and wildcard matching. This section will explain the extent of Lucene syntax support and call out the small amount of unsupported features.


Terms are what values to search for in the records. They can be specified as either a string of text or a number. When searching for a single word, it is not necessary to use quotes. When searching for a phrase, quotes can be used, such “yellow submarine”.

It is not necessary to specify which field(s) to search under. The default is to search all fields.

To search for a term, simply use it, like: cat or 123. Phrases just need double quotes, such as: "cat food".

Terms that in the ISO 8601 format will be interpreted as dates. This is an international format that takes the form of 2018-10-30T12:48:29Z. A complete description of this format can be found at

Terms that in the form of a number, such as 123 or 123.123 will be interpreted as numbers.

Terms can also be interpreted as Internet Protocol address, such as


It is possible to limit what fields to search within. To do so, simply specify the field name followed by a color, such as: animal:cat, size:123, or eats:"cat food".


Wild cards are supported for string terms, but only at the end of the term. For example: animal:cat*. Wildcards are not supported in the beginning or middle of a term, which is different than what Lucene normally supports.


It is possible to search within a range of terms. Simply surround the two terms with square brackets, separated by TO. For example, size:[2 TO 10] will search for all sizes with a number from 2 to 10, inclusive. Exclusive searches can be specified by using curly braces, such as: size:{1 TO 11}. Additionally, it is possible to perform an inclusive search on text terms, such as: name:[aardvark TO zebra].

Boolean Operators

The following operators are supported: AND, OR, and NOT. The default operator is AND. For example, the search bob jones is equivalent to bob AND jones. An example AND search would be: animal:cat AND owner:bob. An example NOT search is: NOT animal:cat or NOT size:12.

AND, OR, and NOT can also be specified using &&, ||, and !, respectively.


A search be be logically grouped by using parenthesis. For example, the queries (animal:cat OR animal:dog) AND owner:sally and animal:cat OR (animal:dog AND owner:sally) are not the same. The first search finds all cats and dogs owned by sally. The second search finds all cats, or all dogs owned by sally.

Escaping Special Characters

Characters that are search keywords such as :, (, and ) can be escaped with a forward slash. For example, to search for a term that includes a parenthesis, the parenthesis can be escaped with \: animal:\(four legs\). Here are all of the reserved search keywords: + - && || ! ( ) { } [ ] ^ " ~ * ? : \.

Unsupported Lucene Features

Relevance ranking: Matching records that are returned from Koverse are not sorted in any particular order.

However, when paging is used, the results are returned in a consistent order. For example, when requesting a page multiple times, the same results are returned. Thus, it is possible to show the user the first page of results and allow them to then navigate to other pages. When doing so, the user will see the same records for each page every time they request them. What is not possible is to sort those results globally. However, a page’s worth of records could be sorted by the client program.

Unsupported Lucene Syntax

The full Lucene syntax can be read online at .

However, note that the following features are not supported in Koverse:

  • Any wildcard searches other than suffix-based.

  • Single character wildcard searches.

  • Fuzzy searches.

  • Proximity searches.

  • Term boosting.

  • The “required” operator +.

  • Field grouping.

Object Search Syntax

For searches that are not written by end-users on the fly but that are constructed programmatically by a web application, we recommend using Koverse’s Object Search Syntax. The Object Search Syntax allows applications to specify search criteria by building a Javascript object, converting to JSON, and submitting to a REST endpoint. This way, a search can be more easily manipulated programmatically by Javascript.

The following table shows the JSON syntax for various types of searches:

Search Criteria

Query Syntax

Searching ‘any’ field for a value

{“$any”: “fmv”}

Search specific field for a value

{“”: “fmv”}

Search AND

{“$and”: [{“$any”: “fmv”}, {“$any”: “blue”}]}

Search OR

{“$or”: [{“$any”: “fmv”}, {“$any”: “blue”}]}

These searches allow various criteria to be combined using operators like AND and OR. Note that the terms of these search are all ‘point’ terms, meaning they specific an exact value. Searching for a range of values is also supported.

Searching Ranges

To search for a range of values, use one of the range operators such as $gte, greater than or equals, etc. A few types of ranges are listed in the following table:

Search Criteria

Query Syntax

Any value greater than or equal to 160

{ “$any”: { “$gte”: 160 }}

Date field less than a specific date

{ “date_created”: { “$lt”: “1980-01-01T00:00:00.000Z }}

Geo Range

{ “fieldName”: { “$box”: [[sw-lat, sw-long],[ne-lat, ne-long]]}}

{ “fieldName”: { “$box” :[[39.5, -104.9],[40, -104.5]] }}

Any value except for 100

{ “$not”: { “amount”: 100 } }

The official list of operators includes:


greater than


greater than or equal to


less than


less than or equal to


equal to


used in place of a field to search for a value in any field


used to negate a search criterion. Note that this results in two ranges being searched, those ‘above’ and ‘below’ the value specified.

Note that queries that combine a range with any other criteria, and queries that combine multiple ranges require Composite Indexes on the fields involved. See Indexing Policy and Composite Indexes below for information on building these.

Indexing Policy and Composite Indexes

By default, all fields in the Records of Koverse Data Sets are indexed. This allows data to easily be discovered by searching across all fields and values. There are times when you may want to change this default indexing policy. You may want to add composite indexes when your searches use more than one search term as they can greatly improve search performance. There also may be times when you want to disable fields from being indexed as they never will be used in searches. While Koverse is designed to efficiently ingest and index data, indexes still aren’t free in terms of disk usage and ingest throughput, and the impact of these costs can sometimes be seen in high volume ingest environments.

To change the current indexing policy, including adding composite indexes, use the Koverse REST API with the resource


An HTTP GET will return the currently configured indexing policy for the Data Set. An HTTP PUT will update the indexing policy based on the body of the request. Several example JSON bodies are seen below. Using a tool like Postman in Google Chrome is an easy way to make REST API calls to Koverse as it will reuse your existing session if you are already logged into the Koverse UI.

Add two composite indexes

This example shows adding two composite indexes. One on the ‘eventType’ and ‘timestamp’ fields, and one on the ‘location’ and ‘timestamp’ fields:

      "fieldsInclusive": false,
      "fields": [],
      "compositeIndexes": [
    { "fieldName": "eventType", "fieldType": "java.lang.String" },
    { "fieldName": "timestamp", "fieldType": "java.lang.Number" }
    { "fieldName": "location", "fieldType": "" },
    { "fieldName": "timestamp", "fieldType": "java.lang.Number" }
            "createValueOnlyIndices": true,
            "dataSetId": "my_dataset_20170308_234200_037"

When creating composite indexes, a “fieldType” is required. This specifies the type of values which the index applies to. Internally Koverse is using Java types for the values in Records and that is why Java class names are seen in the “fieldType” values in the examples. The following types are supported for composite indexes

  • java.lang.String

  • java.lang.Number

  • java.util.Date



Disabling indexing on a field

In this example we turn off indexing on the field ‘version’:

        "fieldsInclusive": false,
        "fields": [ "version" ],
        "compositeIndexes": [],
        "createValueOnlyIndices": true,
        "dataSetId": "my_dataset_20170308_234200_037"