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Loading from Local File

Uploading your local data files to a stage or bucket before loading them into Databend can be unnecessary. Instead, you can use BendSQL, the Databend native CLI tool, to directly import the data. This simplifies the workflow and can save you storage fees. By using BendSQL to import your local data, you can streamline the process and avoid unnecessary steps. Please note that the files must be in a format supported by Databend, otherwise the data cannot be imported. For more information on the file formats supported by Databend, see Input & Output File Formats.

Tutorial 1 - Load from a Local File​

This tutorial takes a CSV file as an example, showing how to load data into Databend from a local file.

Before You Begin​

Download and save the sample file books.csv to a local folder. The file contains two records:

Transaction Processing,Jim Gray,1992
Readings in Database Systems,Michael Stonebraker,2004

Step 1. Create Database and Table​

> bendsql
Welcome to BendSQL.
Trying connect to localhost:8000 as user root.
Connected to DatabendQuery v1.1.2-nightly-8ade21e4669e0a2cc100615247705feacdf76c5b(rust-1.70.0-nightly-2023-04-15T16:08:52.195357424Z)

root@localhost> CREATE DATABASE book_db;
Processed in (0.020 sec)

root@localhost> use book_db;

USE book_db

0 row in 0.020 sec. Processed 0 rows, 0B (0 rows/s, 0B/s)

root@localhost> CREATE TABLE books
(
    title VARCHAR,
    author VARCHAR,
    date VARCHAR
);
Processed in (0.029 sec)

root@localhost>

Step 2. Load Data into Table​

Send loading data request with the following command:

> bendsql --query='INSERT INTO book_db.books VALUES;' --format=csv --data=@books.csv --progress
==> Stream Loaded books.csv:
    Written 2 (24.29 rows/s), 157B (1.86 KiB/s)

Step 3. Verify Loaded Data​

> echo "SELECT * FROM books;" | bendsql --database book_db
┌─────────────────────────────────────────────────────────────┐
│             title            │        author       │  date  │
│            String            │        String       │ String │
├──────────────────────────────┼─────────────────────┼────────┤
│ Transaction Processing       │ Jim Gray            │ 1992   │
│ Readings in Database Systems │ Michael Stonebraker │ 2004   │
└─────────────────────────────────────────────────────────────┘

Tutorial 2 - Load into Specified Columns​

In Tutorial 1, you created a table containing three columns that exactly match the data in the sample file. You can also load data into specified columns of a table, so the table does not need to have the same columns as the data to be loaded as long as the specified columns can match. This tutorial shows how to do that.

Before You Begin​

Before you start this tutorial, make sure you have completed Tutorial 1.

Step 1. Create Table​

Create a table including an extra column named "comments" compared to the table "books":

CREATE TABLE bookcomments
(
    title VARCHAR,
    author VARCHAR,
    comments VARCHAR,
    date VARCHAR
);

Step 2. Load Data into Table​

Send loading data request with the following command:

> bendsql --query='INSERT INTO book_db.bookcomments(title,author,date) VALUES;' --format=csv --data=@books.csv --progress
==> Stream Loaded books.csv:
    Written 2 (23.23 rows/s), 221B (2.51 KiB/s)

Notice that the query part above specifies the columns (title, author, and date) to match the loaded data.

Step 3. Verify Loaded Data​

SELECT * FROM bookcomments;

┌────────────────────────────────────────────────────────────────────────┐
│             title            │        author       │ comments │  date  │
│            String            │        String       │  String  │ String │
├──────────────────────────────┼─────────────────────┼──────────┼────────┤
│ Transaction Processing       │ Jim Gray            │          │ 1992   │
│ Readings in Database Systems │ Michael Stonebraker │          │ 2004   │
└────────────────────────────────────────────────────────────────────────┘

2 rows in 0.033 sec. Processed 2 rows, 2B (60.42 rows/s, 7.14 KiB/s)