Using the GigaSpaces Web Notebook

This section describes how to use the interactive Apache Zeppelin Web Notebook with GigaSpaces.

Starting the Web Notebook

The GigaSpaces Apache Zeppelin web notebook can be started in any of the following ways:

  • Run the insightedge demo command; the web notebook is started automatically at localhost:9090.

  • Start the web notebook manually at any time by running from the $GS_HOME/insightedge/zeppelin/bin directory.

When Apache Zeppelin is running, you can browse to localhost:9090 and start exploring the pre-built notebooks:


Connecting a New Apache Zeppelin Notebook to GigaSpaces

If you want to create a new Apache Zeppelin web notebook instead of using the example notebooks that come packaged with GigaSpaces, there are two ways to run a Zeppelin notebook against GigaSpaces:

  • Write a Spark application that reads and writes data to the data grid using the Spark context.

  • Write an SQL query that is interpreted by the GigaSpaces JDBC interpreter (which is run directly against the data grid).

Initializing the Spark Context

In order to establish the connection between Apache Zeppelin through Apache Spark and then to the data grid, each notebook should start with a paragraph that injects the GigaSpaces settings to the Spark context. Important settings include the following properties:

  • spaceName

  • lookupGroups

  • lookupLocators

These properties are injected through the following in the notebook:

  • InsightEdge class:

        case class InsightEdgeConfig(
                                     spaceName: String,
                                     lookupGroups: Option[String] = None,
                                     lookupLocators: Option[String] = None)
  • Apache Zeppelin mandatory initialization paragraph:

        import org.insightedge.spark.implicits.all._
        import org.insightedge.spark.context.InsightEdgeConfig
        //spaceName is required, other two parameters are optional
        val ieConfig = new InsightEdgeConfig(spaceName = "mySpace", lookupGroups = None, lookupLocators = None)
        //sc is the spark context initalized by zeppelin

GigaSpaces JDBC Interpreter

Apache Zeppelin uses interpreters to compile and run paragraphs. The Apache Zeppelin instance that is packaged with GigaSpaces comes with a custom JDBC interpreter that enables running SQL queries directly on the data grid using the web notebook. The queries are executed by the InsightEdge SQL Driver.

Configuring the JDBC Interpreter

The JDBC interpreter connects to the data grid via a JDBC URL. To configure the URL value to point to the data grid, do the following:

  1. In the Apache Zeppelin web interface, navigate to the Interpreters section.

  2. Select the insightedge_jdbc interpreter, and click Edit.

  3. Edit the default.url parameter as follows: jdbc:insightedge:spaceName=<space-name>

  4. Save the changes you made to the interpreter.

Querying the Data Grid in Notebooks

When the JDBC interpreter is properly configured, Zeppelin paragraphs that are bound to the %insightedge_jdbc interpreter can run SQL queries directly on the data grid.

Querying Multiple JDBC Data Sources

You can configure the JDBC interpreter to query multiple JDBC data sources (in addition to the default data source). You define the additional data sources in the notebook by adding the following properties to the interpreter for each data source:

  • <data-source-name>.driver - The class of JDBC driver applicable to the data source

  • <data-source-name>.url - The JDBC connection string to the data source

After saving your changes, Zeppelin paragraphs starting with %insightedge_jdbc(<data-source-name>) can run queries on the data sources that you added.

For example, let's say we want to query 3 data grid sources:

  • "grid_A" (this is the default data source)

  • "grid_B"

  • "grid_C"

Configure Apache Zeppelin in the interpreter section to enable querying one or more of these data sources with the GigaSpaces JDBC interpreter. The following key/value pairs enable querying the specified data sources:

grid_A configuration:

  • Key = default.driver, Value = com.gigaspaces.jdbc.Driver

  • Key = default.url, Value = insightedge:jdbc:url:spaceName=grid_A

Paragraphs starting with %insightedge_jdbc will query Grid A.

grid_B configuration:

  • Key = B.driver, Value = com.gigaspaces.jdbc.Driver

  • Key = B.url, Value = insightedge:jdbc:url:spaceName=grid_B

Paragraphs starting with %insightedge_jdbc will query Grid B.

grid_C configuration:

  • Key = C.driver, Value = com.gigaspaces.jdbc.Driver

  • Key = C.url, Value = insightedge:jdbc:url:spaceName=grid_C

Paragraphs starting with %insightedge_jdbc will query Grid C.

Using the Web Notebook

The Apache Zeppelin web notebook comes with sample notes. We recommend that you review them, and then use them as a template for your own notes. There are several things you should take into account.

  • The data grid model can be declared in a notebook using the %define interpreter:

    package model.v1
    import org.insightedge.scala.annotation._
    import scala.beans.{BeanProperty, BooleanBeanProperty}
    case class Product(
        @BeanProperty @SpaceId var id: Long,
        @BeanProperty var description: String,
        @BeanProperty var quantity: Int,
        @BooleanBeanProperty var featuredProduct: Boolean
        ) {
        def this() = this(-1, null, -1, false)
    import model.v1._
  • You can load external .JARs from the Spark interpreter settings, or with the z.load("/path/to.jar") command:


    For more details, refer to Zeppelin Dependency Management.

  • You must load your dependencies before you start using the SparkContext (sc) command. If you want to redefine the model or load another .JAR after SparkContext has already started, you must reload the Spark interpreter.