5-Minute Quick Start

After completing this tutorial, you will be able to:

• Start a complete Doris cluster within 5 minutes using Docker
• Connect to the cluster with a MySQL client and verify node status
• Create a database and table, and run your first data query

Choose your deployment method

• Want a quick experience? Use Docker deployment, ready in 5 minutes.
• Want a full understanding of production deployment? Use the local full deployment, including FE/BE separation configuration.

Quick deployment with Docker

Starting from the latest version, you can use Docker for quick deployment.

Step 1 (1/3): Download the startup script

Download the script, then run the following command to grant execute permission:

chmod 755 start-doris.sh

Step 2 (2/3): Start the cluster

Run the script to start the cluster (the default version is 4.0.1):

bash start-doris.sh

To specify a version, use the -v parameter:

bash start-doris.sh -v 4.1.0

Step 3 (3/3): Verify cluster status

Connect to the cluster with a MySQL client and check the FE and BE status:

-- Purpose: verify that the FE node has joined the cluster
-- Expected: both Join and Alive columns are true
mysql -uroot -P9030 -h127.0.0.1 -e 'SELECT `host`, `join`, `alive` FROM frontends()'

-- Purpose: verify that the BE node is heartbeating normally
-- Expected: the Alive column is 1
mysql -uroot -P9030 -h127.0.0.1 -e 'SELECT `host`, `alive` FROM backends()'

Output explanation: Alive=true (FE) or Alive=1 (BE) indicates that the node is running normally.

---

Local full deployment

Environment requirements

• Operating system: mainstream AMD/ARM Linux environments such as Ubuntu
• Java environment: JDK 17+
• User permissions: create a dedicated Doris user; do not use root

Step 1 (1/4): Download the binary package

Download the binary package for your system from the Apache Doris download page, and extract it to a directory of your choice.

Step 2 (2/4): Configure the system environment

Increase the maximum number of file handles (to avoid errors caused by too many open files):

vi /etc/security/limits.conf
* soft nofile 1000000
* hard nofile 1000000

Increase the virtual memory area limit:

cat >> /etc/sysctl.conf << EOF
vm.max_map_count = 2000000
EOF
sysctl -p

Step 3 (3/4): Deploy the FE

1. Configure the FE: edit apache-doris/fe/conf/fe.conf

   # Specify the Java environment
   JAVA_HOME=/home/doris/jdk
   
   # Specify the FE listening IP (adjust based on the actual network segment)
   priority_networks=127.0.0.1/32

2. Start the FE:

   apache-doris/fe/bin/start_fe.sh --daemon

3. Verify the FE status:

   -- Purpose: confirm that the FE has started and joined the cluster
   -- Expected: Join=true, Alive=true, IsMaster=true
   mysql -uroot -P9030 -h127.0.0.1 -e "show frontends;"

Step 4 (4/4): Deploy the BE

1. Configure the BE: edit apache-doris/be/conf/be.conf

   # Specify the BE listening IP (must be in the same network segment as the FE's priority_networks)
   priority_networks=127.0.0.1/32

2. Start the BE:

   apache-doris/be/bin/start_be.sh --daemon

3. Register the BE with the cluster:

   -- Purpose: add the BE node to the cluster
   ALTER SYSTEM ADD BACKEND "127.0.0.1:9050";

4. Verify the BE status:

   -- Purpose: confirm that the BE is registered and heartbeating normally
   -- Expected: Alive=true
   mysql -uroot -P9030 -h127.0.0.1 -e "show backends;"

---

Run your first query

Whether you used Docker or a local deployment, once the cluster is up you can follow the steps below to try out Doris SQL features.

Connect to the cluster

mysql -uroot -P9030 -h127.0.0.1

Create a database and table

-- Purpose: create a demo database and table
create database demo;
use demo;

create table mytable
(
    k1 TINYINT,
    k2 DECIMAL(10, 2) DEFAULT "10.05",
    k3 CHAR(10) COMMENT "string column",
    k4 INT NOT NULL DEFAULT "1" COMMENT "int column"
)
COMMENT "my first table"
DISTRIBUTED BY HASH(k1) BUCKETS 1
PROPERTIES ("replication_num" = "1");

Load test data

-- Purpose: insert a few rows of test data
insert into mytable values
(1, 0.14, 'a1', 20),
(2, 1.04, 'b2', 21),
(3, 3.14, 'c3', 22),
(4, 4.35, 'd4', 23);

Run a query

-- Purpose: verify that the data was loaded successfully
-- Expected: 4 rows are returned
select * from demo.mytable;

Sample output:

+------+------+------+------+
| k1   | k2   | k3   | k4   |
+------+------+------+------+
|    1 | 0.14 | a1   |   20 |
|    2 | 1.04 | b2   |   21 |
|    3 | 3.14 | c3   |   22 |
|    4 | 4.35 | d4   |   23 |
+------+------+------+------+

---

FAQ

Q: Is Docker deployment suitable for production?

No. Docker deployment is intended only for local development and testing; data is lost when the container is destroyed. For production, use the local full deployment or a multi-node deployment.

Q: How do I install Docker on Mac?

Download and install Docker Desktop.

Q: After installing Docker Desktop on Mac, I see "Docker environment not detected". What should I do?

Create a symbolic link:

sudo ln -s /Applications/Docker.app/Contents/Resources/bin/docker /usr/local/bin/docker

Q: Docker on Mac reports "error getting credentials". What should I do?

As a temporary workaround, remove the credsStore field from ~/.docker/config.json. Note: this stores credentials in plain text and is for local development only.

Q: A BE node still shows "Dead" after being added. What should I check?

Check whether the BE's priority_networks is in the same network segment as the FE, and confirm that the BE ports (9050/9060/8040/8060) are not blocked by a firewall.

Q: How do I confirm that the cluster is healthy overall?

Run SHOW FRONTENDS; and SHOW BACKENDS;, and ensure that the Alive column is true for every node.

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Next steps

• [Data modeling guide]: learn about Doris data models and partitioning strategies (NEXT-TODO)
• [Getting started with SQL operations]: learn data loading, querying, and updates (NEXT-TODO)
• [Cluster management]: master production-grade cluster operations (NEXT-TODO)

Warning (applies to local deployment only)

The following content is for local development and testing only. Do not use it in production:

1. Data is easily lost: Docker deployments lose data when the container is destroyed; single-replica instances have no data redundancy.
2. Single-replica configuration: the table creation statements in the examples all use a single replica. In production, use multi-replica storage to ensure data reliability.