• Developer guide
  • API reference

›Getting started

Getting started

  • Introduction to Imply Polaris
  • Quickstart
  • Execute a POC
  • Create a dashboard
  • Navigate the console
  • Customize Polaris
  • Key concepts

Tables and data

  • Overview
  • Introduction to tables
  • Table schema
  • Ingestion jobs

    • Create an ingestion job
    • Ingest using SQL
    • Job auto-discovery
    • Timestamp expressions
    • SQL ingestion reference
    • Ingestion status reference
  • Data partitioning
  • Introduction to rollup
  • Replace data
  • Ingestion use cases

    • Approximation algorithms
    • Ingest earliest or latest value

Ingestion sources

  • Ingestion sources overview
  • Supported data formats
  • Create a connection
  • Ingest from files
  • Ingest data from a table
  • Ingest from S3
  • Ingest from Kafka and MSK
  • Ingest from Kinesis
  • Ingest from Confluent Cloud
  • Kafka Connector for Imply Polaris
  • Push event data
  • Connect to Confluent Schema Registry
  • Ingestion source reference

Analytics

  • Overview
  • Manage data cubes
  • Visualize data
  • Data cube dimensions
  • Data cube measures
  • Dashboards
  • Visualizations reference
  • Set up alerts
  • Set up reports
  • Embed visualizations

Querying

  • Overview
  • Time series functions

Monitoring

  • Overview
  • Monitoring dashboards
  • Monitor performance metrics
  • Integrate with Datadog
  • Integrate with Prometheus
  • Integrate with Elastic stack
  • Metrics reference

Management

  • Overview
  • Pause and resume a project

Usage and Billing

  • Billing structure overview
  • Polaris plans
  • Add a payment method
  • Monitor account usage

Security

    Polaris access

    • Overview
    • Invite users to your organization
    • Manage users
    • Permissions reference
    • Manage user groups
    • Enable SSO
    • SSO settings reference
    • Map IdP groups

    Secure networking

    • Connect to AWS
    • Create AWS PrivateLink connection

Developer guide

  • Overview
  • Security

    • Overview
    • Authenticate with API keys
    • Authenticate with OAuth
    • Manage users and groups
    • Restrict an embedding link
  • Migrate deprecated resources
  • Create a table
  • Upload files
  • Ingestion jobs

    • Create an ingestion job
    • Create a streaming ingestion job
    • Ingest using SQL
    • View and manage jobs

    Ingestion sources

    • Ingest from files
    • Ingest from a table
    • Get ARN for AWS access
    • Ingest from Amazon S3
    • Ingest from Kafka and MSK
    • Ingest from Amazon Kinesis
    • Ingest from Confluent Cloud
    • Push event data
    • Kafka Connector for Imply Polaris
    • Kafka Connector reference

    Ingestion use cases

    • Filter data to ingest
    • Ingest nested data
    • Ingest and query sketches
    • Specify data schema
    • Ingest Kafka metadata

    Analytics

    • Query data
    • Connect over JDBC
    • Link to BI tools
    • Query parameters reference
  • Update a project
  • API documentation

    • OpenAPI reference
    • Query API

    Migrations

    • Migrate from Hybrid

Product info

    Release notes

    • 2023
    • 2022
  • Known limitations
  • Druid extensions

Quickstart

This quickstart shows you how to use the Imply Polaris web interface to ingest, query, and visualize data.

For a high-level overview of Polaris components, see Key concepts.

Prerequisites

Before you use this quickstart, make sure you have:

  • A Polaris account
  • One of the supported browsers:
    • Last three versions of Chrome, Firefox, Edge (Chromium version), Opera
    • Firefox ESR
    • Safari (desktop) 14.1 or above

Sign up for an account

If you don't already have a Polaris account, sign up for a limited trial:

  1. Go to https://signup.imply.io.

  2. Enter your information in the sign-up form. Polaris sign-up form

    Your organization name must meet the following criteria:

    • It must contain a minimum of 3 and a maximum of 63 characters. Characters are letters, numbers, and dashes.
    • It must begin with a letter or a number and end with a letter or a number.
    • It cannot start or end with a dash.
    • It cannot contain symbols such as asterisks, underscores, and exclamation points.
    • It cannot end with -imply-cloud.

Polaris doesn't accept free email addresses for new accounts.

  1. Click Sign up.
  2. Check your inbox for a confirmation email from Imply. You must verify your email address to create an account. If you do not receive a confirmation email or have trouble signing up, please contact Polaris Support.

After you've verified your email address, you should receive a welcome email from Imply containing a link to your Polaris account. Click on the link in the email to access your account.

At first login, you are prompted to choose a cloud region in which Imply will host your project.

Polaris supports the following regions:

  • us-east-1: US East (N. Virginia)
  • us-west-2: US West (Oregon)
  • eu-central-1: Europe (Frankfurt)
  • eu-west-1: Europe (Ireland)

Polaris can only host a single project for you in each region.

Load data

This section explains how to load batch data into a table so you can start using Polaris quickly. See Table schema to learn about table design.

Download the sample data

Download a day of clickstream activity from KoalasToTheMax.com. This newline-delimited JSON file is the source data for the quickstart. See Supported data formats for more information on data and file format support in Polaris.

Create a table

To create a table, follow these steps:

  1. Click Tables in the left pane.
  2. Click Create table in the top-right corner.
  3. Enter Koalas to the Max for the table name. If Koalas to the Max is in use, add a number to make your table name unique. Table names must be unique. Once you create a table, you can't change its name.
  4. This quickstart doesn't use aggregations, so leave the Table type as Detail. See Types of tables to learn more.
  5. Click Create.

Upload a file and view sample data

  1. On the table detail page, click Load data > Insert data.

  2. The left pane shows the options source data. Click Files in the BATCH section.

  3. Click Upload files from your computer and choose the file you downloaded, kttm-2019-08-19.json.gz. You can select multiple files for a single ingestion job. However, for the purposes of the tutorial, choose only the one file. Note that file names must be unique.

  4. When the upload is complete, click Next. Polaris samples your data and displays the input field names and data types—for example:

    • continent is a string.
    • session_length is in long format.
  5. At this point you could add input fields, remove input fields, or adjust the data types. For the purposes of the tutorial, click Continue to proceed with ingestion.

Map input fields to Polaris columns

Polaris uses your sample data to identify the input format and suggest a schema for your target table. For the purposes of the tutorial, accept the automatic mapping.

  1. Verify the timestamp column.

    In this case, Polaris suggests the input field timestamp for the __time timestamp column which is correct. To learn about time column handling in Polaris, see Timestamp expressions.

  2. Optionally, edit the column properties for how you want Polaris to store them. For example, you can change the column Name or Data type.

    You can also set the Input expression to alter the values for the column. By default, Polaris maps the input field directly to a column with the same name. To alter the value, you can apply a scalar expression—for example, UPPER("country") to store country values in uppercase.

  3. When you're ready to start your ingestion job, click Start ingestion.

Polaris displays the ingestion job status at the top of the page. When the ingestion job status changes to Completed, you can start querying your data. This can take a few minutes.

Query data

Now that you have ingested data to Polaris, you're ready to run some queries.

  1. On the table detail page, click Query > SQL console. Or, from the home page, click SQL in the left sidebar.

  2. Look for the dataset you just uploaded by table name. Polaris SQL page

  3. Click the arrow next to the table name to see the table's columns.

  4. Enter the following query in the query window:

    SELECT * FROM "Koalas to the Max"
    WHERE "__time" BETWEEN TIMESTAMP '2019-08-19 00:00:00' AND TIMESTAMP '2019-08-21 00:00:00'
    
  5. Click Run.

Instead of returning all of the columns in the table, you can select individual columns by name—for example, you can run the following query to show just the cities:

SELECT "city" FROM "Koalas to the Max"
WHERE "__time" BETWEEN TIMESTAMP '2019-08-19 00:00:00' AND TIMESTAMP '2019-08-20 00:00:00'

Visualize data

Visualization features let you explore and draw insights from your data. There are many types of visualizations available in Polaris, including table view, line chart, and heatmap. See Visualizations reference for details of all visualizations.

Create a data cube

Data cubes contain data from one or more data sources and provide an interface to explore a data set. Make a data cube for Koalas to the Max:

  1. Return to the Home page and click Data cubes from the left sidebar.
  2. Click New data cube.
  3. Select From table as your source and select the table you created, Koalas to the Max. Leave Auto-fill dimensions and measures checked.
  4. Click Next: Create data cube.
  5. Click Save. The data cube appears: Polaris data cube
  6. You can use the data cube to view aggregated data. To view the number of events by country, drag the Country dimension from the left pane into the Show field in the center of the page.

Create a dashboard

Using a dashboard, you can create effective and focused data visualizations. Add a dashboard for the Koalas to the Max data cube:

  1. Return to the Home page and click Dashboards in the left sidebar.
  2. Click New dashboard.
  3. At the top of the page, give your dashboard a name.
  4. With your mouse or pointer, click and drag across blocks on the page to create a new tile.
  5. In the popup, select content type Table.
  6. From the drop-down list, select the data cube Koalas to the Max.
  7. Add a Row for the Country dimension.
  8. Click elsewhere on the page to close the dialog.
  9. Click Create.

That's it! Continue to explore the Polaris UI, try out your own data, or learn more about creating a schema.

Learn more

See the following topics for more information:

  • Navigate the console to learn about the features of the Polaris UI.
  • Key concepts for reference on Polaris concepts and terminology.
← Introduction to Imply PolarisExecute a POC →
  • Prerequisites
  • Sign up for an account
  • Load data
    • Download the sample data
    • Create a table
    • Upload a file and view sample data
    • Map input fields to Polaris columns
  • Query data
  • Visualize data
    • Create a data cube
    • Create a dashboard
  • Learn more
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