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Pinot Data Explorer is a user-friendly interface in Apache Pinot for interactive data exploration, querying, and visualization. |
Once you have set up a cluster, you can start exploring the data and the APIs using the Pinot Data Explorer.
Navigate to http://localhost:9000 in your browser to open the Data Explorer UI.
The first screen that you'll see when you open the Pinot Data Explorer is the Cluster Manager. The Cluster Manager provides a UI to operate and manage your cluster.
If you want to view the contents of a server, click on its instance name. You'll then see the following:
To view the baseballStats table, click on its name, which will show the following screen:
From this screen, we can edit or delete the table, edit or adjust its schema, as well as several other operations.
For example, if we want to add yearID to the list of inverted indexes, click on Edit Table, add the extra column, and click Save:
Let's run some queries on the data in the Pinot cluster. Navigate to Query Console to see the querying interface.
We can see our baseballStats
table listed on the left (you will see meetupRSVP
or airlineStats
if you used the streaming or the hybrid quick start). Click on the table name to display all the names along with the data types of the columns of the table.
You can also execute a sample query select * from baseballStats limit 10
by typing it in the text box and clicking the Run Query button.
Cmd + Enter
can also be used to run the query when focused on the console.
Here are some sample queries you can try:
select playerName, max(hits)
from baseballStats
group by playerName
order by max(hits) desc
select sum(hits), sum(homeRuns), sum(numberOfGames)
from baseballStats
where yearID > 2010
select *
from baseballStats
order by league
Pinot supports a subset of standard SQL. For more information, see Pinot Query Language.
The Pinot Admin UI contains all the APIs that you will need to operate and manage your cluster. It provides a set of APIs for Pinot cluster management including health check, instances management, schema and table management, data segments management.
Let's check out the tables in this cluster by going to Table -> List all tables in cluster, click Try it out, and then click Execute. We can see thebaseballStats
table listed here. We can also see the exact cURL call made to the controller API.
You can look at the configuration of this table by going to Tables -> Get/Enable/Disable/Drop a table, click Try it out, type baseballStats
in the table name, and then click Execute.
Let's check out the schemas in the cluster by going to Schema -> List all schemas in the cluster, click Try it out, and then click Execute. We can see a schema called baseballStats
in this list.
Take a look at the schema by going to Schema -> Get a schema, click Try it out, type baseballStats
in the schema name, and then click Execute.
Finally, let's check out the data segments in the cluster by going to Segment -> List all segments, click Try it out, type in baseballStats
in the table name, and then click Execute. There's 1 segment for this table, called baseballStats_OFFLINE_0
.
To learn how to upload your own data and schema, see Batch Ingestion or Stream ingestion.