JavaScript Developer Guide

Step-by-step instructions on writing JavaScript applications with Kinetica

The following guide provides step-by-step instructions to get started writing JavaScript applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under JavaScript API Reference.

API Download

The source code for the JavaScript API is available for download from the GitHub repository kineticadb/kinetica-api-javascript. Follow the instructions in the included README file to use the API library.

Connecting to the Database

To connect to the database, instantiate an object of the GPUdb class, providing the connection URL, including host & port of the database server as well as an optional username & password for secure connections:

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var db = new GPUdb([url], {"username": user, "password": pass});

Loading Data

Before any data can be loaded into the system, a Type needs to be defined in the system. The type definition is a JSON string describing the fields (i.e. columns) of the type along with a name for the type. Each field consists of a name and a data type:

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// Declare the data type for the table
var my_type = {
    "type": "record",
    "name": "my_type",
    "fields": [
        {"name":"col1","type":"double"},
        {"name":"col2","type":"string"},
        {"name":"group_id","type":"string"}
    ]
};

// Register the data type with GPUdb and get the type's ID
var create_type_rsp = db.create_type( JSON.stringify( my_type ), "my_type" );
var type_id = create_type_rsp.type_id;

The returned object from the create_type() call contains a unique type identifier allocated by the system. This identifier can then be used in the request to create a new table as follows:

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var create_table_rsp = db.create_table( table_name, type_id );

Once the table is created, data can be inserted as follows:

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// Generate records to be inserted 
var records = [];
for (var i = 0; i < 10; i++) {
    var record = {
        col1 : (i + 0.1),
        col2 : ("string " + i),
        group_id : "Group 1"
    };
    records.push( record );
}

// This option will return IDs per record with which we can refer
// to particular records later as needed
var insert_options = { "return_record_ids" : "true" }
var insert_records_rsp = db.insert_records( table_name, records, insert_options );
console.log( "Record IDs for newly inserted records: " + insert_records_rsp["record_ids"] );

Retrieving Data

Once the table is populated with data, the data can be retrieved from the system by a call to get_records() as shown below:

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var get_records_rsp = db.get_records( table_name );
console.log( "Retrieved records: " );
console.log( JSON.stringify( get_records_rsp["data"] ) );

For large tables, the data can be easily be retrieved in smaller blocks by using the offset and limit parameters. The returned response also contains the schema (or data type) of the results.

Running Queries

To filter a subset of the records, use the filter() method with an expression as follows:

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var filter_rsp = db.filter( table_name, view1_name, "col1 = 1.1" );
console.log( "Number of filtered records: " + filter_rsp["count"] );

To filter all the records matching a known list of values:

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var column_values_map = {
        col1 : [ "1.1", "2.1", "5.1" ]
};

var filter_by_list_rsp = db.filter_by_list( table_name, view2_name, column_values_map );
console.log( "Number of records filtered by list: " + filter_by_list_rsp["count"] );

To retrieve a list of all the unique values for a column or a set of columns or expression:

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var unique_rsp = db.aggregate_unique( table_name, "group_id", 0 )
console.log( "Unique of values in 'group_id': " );
console.log( JSON.stringify( unique_rsp['data'] ) );

Kinetica supports various group-by queries. To group by one or more columns and return the count of the unique values, use the aggregate_group_by() method as shown below. The next query shows how to get the count of records, as well as the sum and average of the values of column col1, within each group:

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var column_names = [ "col2" ];
var group_by_rsp = db.aggregate_group_by( table_name, column_names, 0 )
console.log( "Group by results: " );
console.log( JSON.stringify( group_by_rsp['data'] ) );

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var column_names = [ "group_id", "count(*)", "sum(col1)", "avg(col1)" ];
group_by_rsp = db.aggregate_group_by( table_name, column_names, 0 )
console.log( "Second group by results: " );
console.log( JSON.stringify( group_by_rsp['data'] ) );

Kinetica supports grouping numerical data into a histogram. The input range is divided into equal sized bins and the count of objects in each bin are returned:

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var start = 1.1;
var end = 2;
var interval = 1;

var histogram_rsp = db.aggregate_histogram(table_name, "col1", start, end, interval)
console.log( "Histogram results: " );
console.log( JSON.stringify( histogram_rsp ) );

Download & Run

Included below is a complete example containing all the above requests, the data file, and output.

To run the complete sample, ensure the GPUdb.js & tutorial.js references in the tutorial.html file point to the correct location of the Kinetica Javascript API library & tutorial script files, respectively--(the default assumes all three files are co-located in a browser-accessible location). Then, open the tutorial.html file in a browser, passing the Kinetica URL, as well as optional username/password credentials for the server as URL parameters:

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file:///path/to/tutorial/tutorial.html?url=<url>[&user=<user>&pass=<pass>]

Note

As this script creates a schema and several database objects within it, system admin permission is required to run it.