BigQuery Interpreter for Apache Zeppelin
Overview
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 |
zeppelin.bigquery.sql_dialect | BigQuery SQL dialect (standardSQL or legacySQL). If empty, [query prefix](https://cloud.google.com/bigquery/docs/reference/standard-sql/enabling-standard-sql#sql-prefix) like '#standardSQL' can be used. |
BigQuery API
Zeppelin is built against BigQuery API version v2-rev265-1.21.0 - API Javadocs
Enabling the BigQuery Interpreter
In a notebook, to enable the BigQuery interpreter, click the Gear icon and select bigquery.
Provide Application Default Credentials
Within Google Cloud Platform (e.g. Google App Engine, Google Compute Engine), built-in credentials are used by default.
Outside of GCP, follow the Google API authentication instructions for Zeppelin Google Cloud Storage
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 to build your own SQL.
For Example, SQL to query for top 10 departure delays across airports using the flights public dataset
%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
%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.