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Tutorial - Load from a Local File

In this tutorial, you will load data from a local sample file into Databend with the Streaming Load API.

Tutorial 1 - Load from a CSV 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 the sample CSV file books.csv. The sample contains the following records:

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

Step 1. Create Database and Table

mysql -h127.0.0.1 -uroot -P3307
CREATE DATABASE book_db;
USE book_db;

CREATE TABLE books
(
title VARCHAR,
author VARCHAR,
date VARCHAR
);

Step 2. Load Data into Table

Create and send the API request with the following scripts:

curl -XPUT 'http://root:@127.0.0.1:8081/v1/streaming_load' -H 'insert_sql: insert into book_db.books format CSV' -H 'skip_header: 0' -H 'field_delimiter: ,' -H 'record_delimiter: \n' -F 'upload=@"./books.csv"'

Response Example:

{
"id": "f4c557d3-f798-4cea-960a-0ba021dd4646",
"state": "SUCCESS",
"stats": {
"rows": 2,
"bytes": 157
},
"error": null,
"files": ["books.csv"]
}

Step 3. Verify Loaded Data

SELECT * FROM books;

+------------------------------+----------------------+-------+
| title | author | date |
+------------------------------+----------------------+-------+
| 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. The Streaming Load API also allows you to load data into specified columns of a table in Databend, 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

Create and send the API request with the following scripts:

curl -XPUT 'http://root:@127.0.0.1:8081/v1/streaming_load' -H 'insert_sql: insert into book_db.bookcomments(title,author,date)format CSV' -H 'skip_header: 0' -H 'field_delimiter: ,' -H 'record_delimiter: \n' -F 'upload=@"./books.csv"'

Notice that the insert_sql 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 |
+------------------------------+----------------------+----------+--------+
| Transaction Processing | Jim Gray | | 1992 |
| Readings in Database Systems | Michael Stonebraker | | 2004 |
+------------------------------+----------------------+----------+--------+