bulksearch
Advanced tools
Searching full text with BulkSearch is up to 1,000 times faster than ElasticSearch implementation.
Benchmark Comparison: https://jsperf.com/bulksearch
All Features:
Plugins In Progress:
npm install bulksearch
In your code include as follows:
var BulkSearch = require("BulkSearch");
<html>
<head>
<script src="https://cdn.rawgit.com/nextapps-de/bulksearch/dist/bulksearch.min.js"></script>
</head>
...
AMD
var BulkSearch = require("BulkSearch");
var index = new BulkSearch();
alternatively you can also use:
var index = BulkSearch.create();
BulkSearch.create(OPTIONS)
var index = new BulkSearch({
// default values:
type: "integer",
encode: "icase",
boolean: "and",
strict: false,
ordered: false,
multi: false,
cache: false
});
Index.add_(ID, TEXT)
index.add(10025, "John Doe");
Note: The data type of passed IDs has to be specified on creation. It is recommended to uses to most lowest possible data range here, e.g. use "short" when IDs are not higher than 65,535.
| ID Type | Range of Values | Memory of Index each ~ 100.000 Words |
| Byte | 0 - 255 | 683 kb |
| Short | 0 - 65,535 | 1.3 Mb |
| Integer | 0 - 4,294,967,295 | 2,7 Mb |
| Float | 0 - * (16 digits) | 5,3 Mb |
| String | (unlimited) | 1,3 Mb * char count of IDs |
Index.search(TEXT, LIMIT, CALLBACK)
index.search("John");
index.search("John", 10);
index.search("John", function(result){
// array of results
});
Index.update(ID, TEXT)
index.update(10025, "Road Runner");
Index.remove(ID)
index.remove(10025);
Index.cleanup()
index.cleanup();
Index.destroy()
index.destroy();
Index.init(OPTIONS)
index.init();
Index.addMatcher(KEY_VALUE_PAIRS)
index.addMatcher({
'ä': 'a', // replaces all 'ä' to 'a'
'ö': 'o',
'Ü': 'u'
});
var index = new BulkSearch({
encode: function(str){
// do something with str ...
return str;
}
});
Index.info()
index.info();
Returns information about the index, e.g.:
{
"bytes": 3600356288,
"chunks": 9,
"fragmentation": 0,
"fragments": 0,
"id": 0,
"length": 7798,
"matchers": 0,
"size": 10000,
"status": false
}
Note: When the fragmentation value is about 50% or higher, your should consider using cleanup() to free all fragmented available memory.
Index.cleanup()
index.cleanup();
The required RAM per instance can be calculated as follow:
BYTES = CONTENT_CHAR_COUNT * (BYTES_OF_ID + 2)
Character count may be less related to the phonetic settings (e.g. when using soundex).
Author BulkSearch: Thomas Wilkerling
License: Apache 2.0 License
FAQs
Superfast, lightweight and read-write optimized full text search library.
The npm package bulksearch receives a total of 11 weekly downloads. As such, bulksearch popularity was classified as not popular.
We found that bulksearch demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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