This quickstart shows you how to use the Imply Polaris web interface to load batch file data, query, and visualize data.
For a high-level overview of Polaris components, see Key concepts.
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 Imply Polaris account
If you don't already have a Polaris account, sign up for a limited trial:
- Go to https://signup.imply.io.
- Enter your first and last name, work email, and click Continue.
Polaris doesn't accept free email addresses for new accounts.
- Enter a password and a valid organization name. 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.
- Accept the Terms and Conditions and click Sign up to Imply.
- Check your inbox for a confirmation email from Imply. You must verify your email address to create an organization in Polaris.
If you do not receive a confirmation email or have trouble signing up, please contact Polaris customer support at firstname.lastname@example.org.
Access your organization
Check your inbox for a welcome email from Imply. The email contains a link to your Polaris organization account. Click on the link in the email to access your account.
You can also access your account by going to the following URL:
<organization> placeholder with the name of your organization.
Note that if you try to log in immediately after you sign up, you might have to wait a few minutes for your account to be ready.
When you log in, Polaris displays your home page:
See Navigate the console to learn about the features of the Polaris UI.
This tutorial guides you through the steps to load batch data into a table so you can start using Polaris quickly. To learn more about table design, see Create a schema.
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:
- In the Polaris UI, click Create a table on the home screen.
Koalas to the Maxfor the table name. If
Koalas to the Maxis 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.
- This tutorial doesn't use aggregations, so leave the Table type as Detail. See Types of tables to learn more.
- When you're ready, click Create.
Upload a file and view sample data
Polaris gives you the option to manually define a schema (Edit schema) or Load data. For the purposes of the quickstart, click Load data.
See Create a schema to learn about defining a schema manually.
The left pane shows the options source data. Click Files in the BATCH section.
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.
When the upload is complete, click Next.
Polaris samples your data and displays the input field names and data types. For example:
continentis a string.
session_lengthis a long format.
- 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 Table within Polaris. For the purposes of the tutorial, you'll accept the automatic mapping.
Verify the timestamp column.
In this case, Polaris suggests the input field
__timetimestamp column which is correct. To learn about time column handling in Polaris, see Timestamp.
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. For example, "UNITED STATES" or "BRAZIL."
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 is complete, Polaris shows the data in the table view.
To monitor the status of the ingestion job, click
...* Actions* and select View jobs.
When the ingestion job status changes to COMPLETED, you can start querying your data. This can take a few minutes.
Now that you have ingested data to Polaris, you're ready to run some queries.
- From the table view, click Explore table > SQL editor. Or, from Home page, click SQL in the left sidebar.
- Look for the data set you just uploaded by table name.
- Hover over the table name to display the arrow button. Click on the arrow to populate the SQL QUERY IDE.
- You can remove the
WHEREclause when working with a small amount of data, such as this, but a good practice is to run queries with a time boundary. Replace the default
WHEREclause with the following:
WHERE "__time" BETWEEN TIMESTAMP '2019-08-19 00:00:00' AND TIMESTAMP '2019-08-21 00:00:00'
- Click Run. The query result is similar to the following:
Instead of returning all of the columns in the table, you can select individual columns by name. For example, run the following SQL 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'
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.
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:
- Return to the Home page and click Data cubes from the left sidebar.
- Click New data cube.
- Select From table as your source and select the table you created, Koalas to the Max. Leave Auto-fill dimensions and measures checked.
- Click Next: Create data cube.
- Click Save. The data cube appears:
- 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:
- Return to the Home page and click Dashboards in the left sidebar.
- Click New dashboard.
- At the top of the page, give your dashboard a name.
- With your mouse or pointer, click and drag across blocks on the page to create a new tile.
- In the popup, select content type Table.
- From the drop-down list, select the data cube Koalas to the Max.
- Add a Row for the Country dimension.
- Click elsewhere on the page to close the dialog.
- Click Create.
That's it! Continue to explore the Polaris UI, try out your own data, or learn more about creating a schema.