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Hue is a web-based interactive query editor in the Hadoop stack that lets you visualize and share data.
Figure 1. Impala Query Results in Hue
![](../images/hue_ui_query_editor_trips_511.png)
![](../images/hue_ui_query_editor_trips_511.png)
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Analyze and visualize your data with Impala, a high-speed, low-latency SQL query engine.
![](../static/tip.jpg)
- Log on to Hue: select .
- Download and unzip one year of bike trips from the Bay Area Bike Share program (~80 MB).
- Create a table from ~/babs_open_data_year_1/201402_babs_open_data/201402_trip_data.csv.
- Go to the Metastore Tables Manager (or Tables Browser).
- In the default database, click the Create Table icon
.
- Set Type = File.
- Set Path by dragging 201402_trip_data.csv to the Path field.
- Set Formats (Comma, New Line, Double Quote) and click Next.
- Set Properties Format = Csv.
- Edit Fields and click Submit:
- Change ZipCode to data type string.
- Rename Bike # to Bike ID.
- Click Run
to execute a select query in Hive.
- Go to
- Click Refresh
and select Perform incremental metadata update to display your new table.
- Input a query into the editor, for example:
select `start station`, `end station`, count(*) as trips from `default`.`201402_trip_data` group by `start station`, `end station` order by trips desc;
- Click Format
to make the query multi-line.
- Click Save
, input a query name, and click Save.
- Click Execute
to run the query.
.
- Click Refresh
- Create a Bar chart by clicking
:
- Set the X-axis as start station and the Y-axis as trips. A bar chart displays.
- Set the Limit to 10.
- Create a Pie chart by clicking
.
- Download the results by clicking
and selecting CSV or Excel.
To learn more about the power of Hue, see Hue How-tos.
Page generated September 13, 2018.
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