google-big-queryHow can I use Google Big Query to store and manage my NoSQL data?
Google BigQuery is a powerful cloud-based data warehouse that can be used to store and manage NoSQL data. It supports a wide range of data formats, including JSON, Avro and CSV. To store and manage NoSQL data in BigQuery, you can use the BigQuery service to create a table and load the data into it.
For example, the following code creates a table called “my_table” in BigQuery and loads a JSON file into it:
bq --location=US mk --table --schema my_table.json my_table
bq load --source_format=NEWLINE_DELIMITED_JSON my_table.json gs://my-bucket/my_file.json
The first command creates the table, while the second command loads the JSON file into the table.
In addition, BigQuery includes a SQL-like query language called BigQuery SQL, which can be used to query and analyze the data stored in BigQuery. For example, the following query counts the number of records in the table:
SELECT COUNT(*) FROM my_table
Output example
+-------+
| f0_ |
+-------+
| 10000 |
+-------+
The query language also supports a wide range of operations, such as joins, aggregation, and window functions.
Helpful links
More of Google Big Query
- How do I set up a Google Big Query zone?
- How can I use Google Big Query with Python?
- How can I use Google Big Query to analyze Reddit data?
- How can I use regular expressions in Google Big Query?
- What is Google Big Query?
- How do I set up permissions for Google BigQuery?
- How can I use Google BigQuery to apply machine learning?
- How do I use Google Big Query to merge data?
- How do I set up a primary key in Google BigQuery?
- How can I use Google Big Query to count the number of zeros in a given dataset?
See more codes...