• Developer guide
  • API reference

›Developer guide

Getting started

  • Introduction to Imply Polaris
  • Quickstart
  • Navigate the console
  • Key concepts

Ingestion sources

  • Ingestion sources overview
  • Supported data formats
  • Create a connection
  • Ingest from files
  • Ingest from S3
  • Ingest from Kinesis
  • Ingest from Confluent Cloud
  • Kafka Connector for Imply Polaris
  • Push event data

Tables and data

  • Overview
  • Introduction to tables
  • Table schema
  • Create an ingestion job
  • Timestamp expressions
  • Data partitioning
  • Introduction to rollup
  • Approximation algorithms
  • Replace data

Analytics

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

Monitoring

  • Overview

Management

  • Overview
  • Pause and resume a project

Billing

  • Overview
  • Polaris plans
  • Estimate project costs

Usage

  • Overview

Security

    Polaris access

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

    Secure networking

    • Connect to AWS

Developer guide

  • Overview
  • Authentication

    • Overview
    • Authenticate with API keys
    • Authenticate with OAuth
  • Manage users and groups
  • Migrate deprecated resources
  • Create a table
  • Define a schema
  • Upload files
  • Create an ingestion job
  • Ingestion sources

    • Ingest from files
    • Ingest from a table
    • Get ARN for AWS access
    • Ingest from Amazon S3
    • Ingest from Amazon Kinesis
    • Ingest from Confluent Cloud
    • Push event data
    • Kafka Connector for Imply Polaris
    • Kafka Connector reference
  • Filter data to ingest
  • Ingest nested data
  • Ingest and query sketches
  • Query data
  • Update a project
  • Link to BI tools
  • Connect over JDBC
  • Query parameters reference
  • API documentation

    • OpenAPI reference
    • Query API

Product info

  • Release notes
  • Known limitations
  • Druid extensions

Data cube and dashboard query parameters reference

You can create a URL that links directly to a Polaris data cube or dashboard.

This topic contains a description of the query parameters you can use to define the view of the data cube or dashboard in the link.

URL structure

The URL contains the data cube or dashboard ID, followed by the query parameters that filter the view.

You can locate data cube and dashboard IDs in the Polaris UI.

Data cube URL

https://POLARIS_URL/pivot/i/DATA_CUBE_ID?QUERY_PARAMETER=VALUE&...&QUERY_PARAMETER=VALUE

Dashboard URL

https://POLARIS_URL/pivot/c/DASHBOARD_ID?QUERY_PARAMETER=VALUE&...&QUERY_PARAMETER=VALUE

For example, the following link applies the table visualization with a dimension, measure, and filter to a Wikipedia data cube:

https://example.imply.io/pivot/i/wikipedia-web093b/?visualization=table&dimension=cityName&measure=sum_added&filter=cityName[in](London,Paris)

Reserved characters

Use URL encoding for reserved characters and spaces. For example, represent the hash character in #en.wikipedia as %23: filter=channel[eq]%23en.wikipedia.

See Percent-encoding for more information and a list of reserved characters.

Query parameters

You can use the following query parameters to construct a link to a data cube or dashboard.

Data cube parameters

The following query parameters apply to data cube URLs.

visualization

The visualization to apply to the data cube. You must set a visualization if you want to apply any of the other query parameters or a filter.

  • Value: Visualization name—one of:
    bubble-chart, geo-marks, geo-shade, heatmap, horizontal-bars, line-chart, path-tree, pie-chart, records, records-table, sankey, sparkline, stack-area-chart, street-map, spot-matrix, sunburst, table, totals, treemap, vertical-bars
  • Supports multiple: No

Example to set the visualization type to table: visualization=table

dimension

One or more dimensions to apply to the data cube.

  • Value: Dimension ID
    View dimension info in the Polaris UI to find dimension IDs.
  • Supports multiple: Yes

Example to set dimensions to city name and channel: dimension=cityName&dimension=channel

measure

One or more measures to apply to the data cube.

  • Value: Measure ID
    View measure info in the Polaris UI to find measure IDs.
  • Supports multiple: Yes

Example to set measures to comment length and added: measure=sum_commentLength&measure=sum_added

compare

Include a time comparison—for example, to compare current data with a previous period of time.

  • Value: Date or duration
  • Supports multiple: No

Example to compare data with the previous 6 months: compare=P6M

Dashboard parameters

The following query parameters apply to dashboard URLs.

page

Link to a specified dashboard page.

Before you use the page parameter, go to the dashboard options in the Polaris UI and make sure Pages is set to Show pages selector. See Dashboard pages for more information.

  • Value: Dashboard page ID
    Polaris numbers dashboard pages 1, 2, 3, etc as they appear from top to bottom in the UI.
  • Supports multiple: No

Example to display the second dashboard page: page=2

Filter expressions

You can add filter expressions to both data cube and dashboard URLs. Polaris supports the following expressions:

String

  • Operators:
    Equal to: eq
    Contains: contains
    In: in
    Not equal to: ne

Examples:

Filter for city name equal to "London": filter=cityName[eq]London
Filter for city name containing the characters "Lon": filter=cityName[contains]Lon
Filter for city name "London" or "New York": filter=cityName[in](London,New%20York)
Filter for city names not equal to "London" or "New York": filter=cityName[ne](London,New%20York)

Number

  • Operators:
    Greater than: gt
    Less than: lt
    Greater than or equal to: gte
    Less than or equal to: lte
    Provide both upper and lower limits

Example to filter for comment length greater than 10 characters and less than 20 characters: filter=commentLength[gt]10[lt]20

Boolean

  • Operator: eq

Example to filter for records with the "isNew" flag set to "true": filter=isNew[eq]true

Time

  • Operators:
    Start date and time: start
    End date and time: end
    Latest interval: latest
    Previous interval: previous
    Current interval: current
    Provide both start and end to define a fixed time interval—you can't use these operators alone.
  • Valid intervals:
    latest: 1hour, 6hours, 1day, 7days, 30days, 3months
    previous: hour, day, month, quarter, year
    current: hour, day, week, month, quarter, year

Examples:

Filter for records with timestamp between and including 2022-01-01 and 2022-01-02: filter=__time[start]2022-01-01[end]2022-01-02
Filter for records with timestamp set to the previous day: filter=__time[previous]day

← Connect over JDBCOpenAPI reference →
  • URL structure
    • Data cube URL
    • Dashboard URL
    • Reserved characters
  • Query parameters
    • Data cube parameters
    • Dashboard parameters
  • Filter expressions
    • String
    • Number
    • Boolean
    • Time
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