--- layout: page title: "BigQuery Interpreter for Apache Zeppelin" description: "BigQuery is a highly scalable no-ops data warehouse in the Google Cloud Platform." group: interpreter --- {% include JB/setup %} # BigQuery Interpreter for Apache Zeppelin
## Overview [BigQuery](https://cloud.google.com/bigquery/what-is-bigquery) is a highly scalable no-ops data warehouse in the Google Cloud Platform. Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast SQL queries against append-only tables using the processing power of Google's infrastructure. Simply move your data into BigQuery and let us handle the hard work. You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data. ## Configuration
Name Default Value Description
zeppelin.bigquery.project_id Google Project Id
zeppelin.bigquery.wait_time 5000 Query Timeout in Milliseconds
zeppelin.bigquery.max_no_of_rows 100000 Max result set size
## BigQuery API Zeppelin is built against BigQuery API version v2-rev265-1.21.0 - [API Javadocs](https://developers.google.com/resources/api-libraries/documentation/bigquery/v2/java/latest/) ## Enabling the BigQuery Interpreter In a notebook, to enable the **BigQuery** interpreter, click the **Gear** icon and select **bigquery**. ### Setup service account credentials In order to run BigQuery interpreter outside of Google Cloud Engine you need to provide authentication credentials, by [following this instructions](https://developers.google.com/identity/protocols/application-default-credentials): - Go to the [API Console Credentials page](https://console.developers.google.com/project/_/apis/credentials) - From the project drop-down, select your project. - On the `Credentials` page, select the `Create credentials` drop-down, then select `Service account key`. - From the Service account drop-down, select an existing service account or create a new one. - For `Key type`, select the `JSON` key option, then select `Create`. The file automatically downloads to your computer. - Put the `*.json` file you just downloaded in a directory of your choosing. This directory must be private (you can't let anyone get access to this), but accessible to your Zeppelin instance. - Set the environment variable `GOOGLE_APPLICATION_CREDENTIALS` to the path of the JSON file downloaded. * either though GUI: in interpreter configuration page property names in CAPITAL_CASE set up env vars * or though `zeppelin-env.sh`: just add it to the end of the file. ## Using the BigQuery Interpreter In a paragraph, use `%bigquery.sql` to select the **BigQuery** interpreter and then input SQL statements against your datasets stored in BigQuery. You can use [BigQuery SQL Reference](https://cloud.google.com/bigquery/query-reference) to build your own SQL. For Example, SQL to query for top 10 departure delays across airports using the flights public dataset ```bash %bigquery.sql SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays FROM [bigquery-samples:airline_ontime_data.flights] group by departure_airport order by 2 desc limit 10 ``` Another Example, SQL to query for most commonly used java packages from the github data hosted in BigQuery ```bash %bigquery.sql SELECT package, COUNT(*) count FROM ( SELECT REGEXP_EXTRACT(line, r' ([a-z0-9\._]*)\.') package, id FROM ( SELECT SPLIT(content, '\n') line, id FROM [bigquery-public-data:github_repos.sample_contents] WHERE content CONTAINS 'import' AND sample_path LIKE '%.java' HAVING LEFT(line, 6)='import' ) GROUP BY package, id ) GROUP BY 1 ORDER BY count DESC LIMIT 40 ``` ## Technical description For in-depth technical details on current implementation please refer to [bigquery/README.md](https://github.com/apache/zeppelin/blob/master/bigquery/README.md).