BigQuery is a serverless data warehouse service provided by Google Cloud Platform. It allows you to store, query and manage large amounts of data in a very efficient and cost-effective way. One of the tasks you may need to perform in BigQuery is to add rows from one table to another. In this article, we will explain how to add table rows to another table in BigQuery with code examples.

There are two main ways to add table rows to another table in BigQuery: using the BigQuery web UI and using the BigQuery API.

Adding Rows to a Table using the BigQuery Web UI

The BigQuery web UI provides a simple and intuitive way to add table rows to another table. Here's how:

1. Log in to the Google Cloud Console and navigate to the BigQuery interface.
2. Select the project and dataset that contains the table you want to add rows to.
3. Click on the table you want to add rows to.
4. Click on the "Edit" button in the toolbar.
5. In the "Edit Table" dialog, click on the "Add" button to add new rows.
6. Enter the data for each column in the table.
7. Click on the "Save" button to save the changes.

Adding Rows to a Table using the BigQuery API

Another way to add table rows to another table in BigQuery is by using the BigQuery API. Here's how:

1. Set up a project and enable the BigQuery API for the project.
2. Install the Google Cloud SDK.
3. Create a new file and open it in a text editor.
4. Enter the following code to add a row to the table:

from google.cloud import bigquery

# Set up a client object
client = bigquery.Client()

# Set up a dataset reference
dataset_ref = client.dataset("my_dataset")

# Set up a table reference
table_ref = dataset_ref.table("my_table")

# Add a new row to the table
row = {"column1": "value1", "column2": "value2"}
errors = client.insert_rows(table_ref, [row])

# Check for errors
if not errors:
    print("New row added to the table.")
else:
    print("Errors: {}".format(errors))

This code will add a new row to the table with two columns named "column1" and "column2". Replace "value1" and "value2" with the actual values for the new row.

Conclusion

In this article, we have explained how to add table rows to another table in BigQuery using the BigQuery web UI and the BigQuery API. Whether you choose to use the web UI or the API, adding rows to a table in BigQuery is a simple and straightforward process. With the power and scalability of BigQuery, you can easily manage and analyze large amounts of data with ease.
Updating Table Rows in BigQuery

Another common task in BigQuery is updating existing rows in a table. There are two main ways to update rows in BigQuery: using the BigQuery web UI and using the BigQuery API.

Updating Rows using the BigQuery Web UI

To update rows using the BigQuery web UI, you can simply select the rows you want to update, modify the values in the cells, and then click the "Save" button to save your changes. Here's the basic process:

1. Log in to the Google Cloud Console and navigate to the BigQuery interface.
2. Select the project and dataset that contains the table you want to update.
3. Click on the table you want to update.
4. Select the rows you want to update.
5. Click on the "Edit" button in the toolbar.
6. Modify the values in the cells.
7. Click on the "Save" button to save your changes.

Updating Rows using the BigQuery API

To update rows using the BigQuery API, you'll need to use the update_rows method of the BigQuery client object. Here's an example:

from google.cloud import bigquery

# Set up a client object
client = bigquery.Client()

# Set up a dataset reference
dataset_ref = client.dataset("my_dataset")

# Set up a table reference
table_ref = dataset_ref.table("my_table")

# Define the rows to update
rows_to_update = [
    bigquery.Row({"column1": "new_value1", "column2": "new_value2"}, {"column3": "key_value"})
]

# Update the rows
errors = client.update_rows(table_ref, rows_to_update)

# Check for errors
if not errors:
    print("Rows updated successfully.")
else:
    print("Errors: {}".format(errors))

In this example, we're updating a row with a new value for "column1" and "column2", while "column3" is used as the key to identify the row to update.

Deleting Table Rows in BigQuery

If you need to delete rows from a table in BigQuery, you can do so using either the BigQuery web UI or the BigQuery API.

Deleting Rows using the BigQuery Web UI

To delete rows using the BigQuery web UI, simply select the rows you want to delete, and then click the "Delete" button in the toolbar. Here's the basic process:

1. Log in to the Google Cloud Console and navigate to the BigQuery interface.
2. Select the project and dataset that contains the table you want to delete from.
3. Click on the table you want to delete from.
4. Select the rows you want to delete.
5. Click on the "Delete" button in the toolbar.
6. Confirm the deletion.

Deleting Rows using the BigQuery API

To delete rows using the BigQuery API, you'll need to use the delete_rows method of the BigQuery client object. Here's an example:

from google.cloud import bigquery

# Set up a client object
client = bigquery.Client()

# Set up a dataset reference
dataset_ref = client.datas
## Popular questions 
1. How do I add rows to a table in BigQuery using the web UI?

To add rows to a table in BigQuery using the web UI, follow these steps:

1. Log in to the Google Cloud Console and navigate to the BigQuery interface.
2. Select the project and dataset that contains the table you want to add to.
3. Click on the table you want to add to.
4. Click on the "Edit" button in the toolbar.
5. Enter the data for the new row(s) in the cells.
6. Click on the "Save" button to save your changes.

2. How do I add rows to a table in BigQuery using the API?

To add rows to a table in BigQuery using the API, use the `insert_rows` method of the BigQuery client object. Here's an example in Python:

from google.cloud import bigquery

Set up a client object

client = bigquery.Client()

Set up a dataset reference

dataset_ref = client.dataset("my_dataset")

Set up a table reference

table_ref = dataset_ref.table("my_table")

Define the rows to add

rows_to_add = [
bigquery.Row({"column1": "value1", "column2": "value2", "column3": "value3"}),
bigquery.Row({"column1": "value4", "column2": "value5", "column3": "value6"}),
# …
]

Add the rows

errors = client.insert_rows(table_ref, rows_to_add)

Check for errors

if not errors:
print("Rows added successfully.")
else:
print("Errors: {}".format(errors))

In this example, we're adding three rows to the table, each with three columns (column1, column2, and column3).

3. Can I add rows to a table in BigQuery from a CSV file?

Yes, you can add rows to a table in BigQuery from a CSV file. You can do this using the BigQuery web UI by uploading the file, or you can use the BigQuery API to load the data directly into a table.

4. How do I add rows to a table in BigQuery from another table?

You can add rows to a table in BigQuery from another table by using a query. For example, you can use the `INSERT INTO` statement to insert data from one table into another table. Here's an example in BigQuery SQL:

Insert data from one table into another table

INSERT INTO my_dataset.my_destination_table
SELECT *
FROM my_dataset.my_source_table

In this example, we're inserting all of the rows and columns from the `my_source_table` into the `my_destination_table`.

5. How do I add rows to a table in BigQuery with a specific schema?

To add rows to a table in BigQuery with a specific schema, you need to create the table with the desired schema first, and then insert data into the table. The schema defines the names, data types, and ordering of the columns in the table.

Here's an example in Python:

from google.cloud import

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