Replicating data

In this example, you’ll learn how to set up a simple ClickHouse cluster which replicates the data. There are five servers configured. Two are used to host copies of the data. The other three servers are used to coordinate the replication of data.

The architecture of the cluster you will be setting up is shown below:

Although it is possible to run ClickHouse Server and ClickHouse Keeper combined on the same server, we strongly recommend using dedicated hosts for ClickHouse keeper in production environments, which is the approach we will demonstrate in this example.Keeper servers can be smaller, and 4GB RAM is generally enough for each Keeper server until your ClickHouse Servers grow large.

Prerequisites

You’ve set up a local ClickHouse server before
You’re familiar with basic configuration concepts of ClickHouse such as configuration files
You have docker installed on your machine

Set up directory structure and test environment

Example filesThe following steps will walk you through setting up the cluster from scratch. If you prefer to skip these steps and jump straight to running the cluster, you can obtain the example files from the examples repository ‘docker-compose-recipes’ directory.

In this tutorial, you will use Docker compose to set up the ClickHouse cluster. This setup could be modified to work for separate local machines, virtual machines or cloud instances as well.Run the following commands to set up the directory structure for this example:

mkdir cluster_1S_2R
cd cluster_1S_2R

# Create clickhouse-keeper directories
for i in {01..03}; do
  mkdir -p fs/volumes/clickhouse-keeper-${i}/etc/clickhouse-keeper
done

# Create clickhouse-server directories
for i in {01..02}; do
  mkdir -p fs/volumes/clickhouse-${i}/etc/clickhouse-server
done

Add the following docker-compose.yml file to the cluster_1S_2R directory:

docker-compose.yml

version: '3.8'
services:
  clickhouse-01:
    image: "clickhouse/clickhouse-server:latest"
    user: "101:101"
    container_name: clickhouse-01
    hostname: clickhouse-01
    volumes:
      - ${PWD}/fs/volumes/clickhouse-01/etc/clickhouse-server/config.d/config.xml:/etc/clickhouse-server/config.d/config.xml
      - ${PWD}/fs/volumes/clickhouse-01/etc/clickhouse-server/users.d/users.xml:/etc/clickhouse-server/users.d/users.xml
    ports:
      - "127.0.0.1:8123:8123"
      - "127.0.0.1:9000:9000"
    depends_on:
      - clickhouse-keeper-01
      - clickhouse-keeper-02
      - clickhouse-keeper-03
  clickhouse-02:
    image: "clickhouse/clickhouse-server:latest"
    user: "101:101"
    container_name: clickhouse-02
    hostname: clickhouse-02
    volumes:
      - ${PWD}/fs/volumes/clickhouse-02/etc/clickhouse-server/config.d/config.xml:/etc/clickhouse-server/config.d/config.xml
      - ${PWD}/fs/volumes/clickhouse-02/etc/clickhouse-server/users.d/users.xml:/etc/clickhouse-server/users.d/users.xml
    ports:
      - "127.0.0.1:8124:8123"
      - "127.0.0.1:9001:9000"
    depends_on:
      - clickhouse-keeper-01
      - clickhouse-keeper-02
      - clickhouse-keeper-03
  clickhouse-keeper-01:
    image: "clickhouse/clickhouse-keeper:latest-alpine"
    user: "101:101"
    container_name: clickhouse-keeper-01
    hostname: clickhouse-keeper-01
    volumes:
     - ${PWD}/fs/volumes/clickhouse-keeper-01/etc/clickhouse-keeper/keeper_config.xml:/etc/clickhouse-keeper/keeper_config.xml
    ports:
        - "127.0.0.1:9181:9181"
  clickhouse-keeper-02:
    image: "clickhouse/clickhouse-keeper:latest-alpine"
    user: "101:101"
    container_name: clickhouse-keeper-02
    hostname: clickhouse-keeper-02
    volumes:
     - ${PWD}/fs/volumes/clickhouse-keeper-02/etc/clickhouse-keeper/keeper_config.xml:/etc/clickhouse-keeper/keeper_config.xml
    ports:
        - "127.0.0.1:9182:9181"
  clickhouse-keeper-03:
    image: "clickhouse/clickhouse-keeper:latest-alpine"
    user: "101:101"
    container_name: clickhouse-keeper-03
    hostname: clickhouse-keeper-03
    volumes:
     - ${PWD}/fs/volumes/clickhouse-keeper-03/etc/clickhouse-keeper/keeper_config.xml:/etc/clickhouse-keeper/keeper_config.xml
    ports:
        - "127.0.0.1:9183:9181"

Create the following sub-directories and files:

for i in {01..02}; do
  mkdir -p fs/volumes/clickhouse-${i}/etc/clickhouse-server/config.d
  mkdir -p fs/volumes/clickhouse-${i}/etc/clickhouse-server/users.d
  touch fs/volumes/clickhouse-${i}/etc/clickhouse-server/config.d/config.xml
  touch fs/volumes/clickhouse-${i}/etc/clickhouse-server/users.d/users.xml
done

The config.d directory contains ClickHouse server configuration file config.xml, in which custom configuration for each ClickHouse node is defined. This configuration gets combined with the default config.xml ClickHouse configuration file that comes with every ClickHouse installation.
The users.d directory contains user configuration file users.xml, in which custom configuration for users is defined. This configuration gets combined with the default ClickHouse users.xml configuration file that comes with every ClickHouse installation.

Custom configuration directoriesIt is a best practice to make use of the config.d and users.d directories when writing your own configuration, rather than directly modifying the default configuration in /etc/clickhouse-server/config.xml and etc/clickhouse-server/users.xml.The line

<clickhouse replace="true">

Ensures that the configuration sections defined in the config.d and users.d directories override the default configuration sections defined in the default config.xml and users.xml files.

Configure ClickHouse nodes

Server setup

Now modify each empty configuration file config.xml located at fs/volumes/clickhouse-{}/etc/clickhouse-server/config.d. The lines which are highlighted below need to be changed to be specific to each node:

<clickhouse replace="true">
    <logger>
        <level>debug</level>
        <log>/var/log/clickhouse-server/clickhouse-server.log</log>
        <errorlog>/var/log/clickhouse-server/clickhouse-server.err.log</errorlog>
        <size>1000M</size>
        <count>3</count>
    </logger>
    <!--highlight-next-line-->
    <display_name>cluster_1S_2R node 1</display_name>
    <listen_host>0.0.0.0</listen_host>
    <http_port>8123</http_port>
    <tcp_port>9000</tcp_port>
    <user_directories>
        <users_xml>
            <path>users.xml</path>
        </users_xml>
        <local_directory>
            <path>/var/lib/clickhouse/access/</path>
        </local_directory>
    </user_directories>
    <distributed_ddl>
        <path>/clickhouse/task_queue/ddl</path>
    </distributed_ddl>
    <remote_servers>
        <cluster_1S_2R>
            <shard>
                <internal_replication>true</internal_replication>
                <replica>
                    <host>clickhouse-01</host>
                    <port>9000</port>
                </replica>
                <replica>
                    <host>clickhouse-02</host>
                    <port>9000</port>
                </replica>
            </shard>
        </cluster_1S_2R>
    </remote_servers>
    <zookeeper>
        <node>
            <host>clickhouse-keeper-01</host>
            <port>9181</port>
        </node>
        <node>
            <host>clickhouse-keeper-02</host>
            <port>9181</port>
        </node>
        <node>
            <host>clickhouse-keeper-03</host>
            <port>9181</port>
        </node>
    </zookeeper>
    <!--highlight-start-->
    <macros>
        <shard>01</shard>
        <replica>01</replica>
        <cluster>cluster_1S_2R</cluster>
    </macros>
    <!--highlight-end-->
</clickhouse>

Directory	File
`fs/volumes/clickhouse-01/etc/clickhouse-server/config.d`	`config.xml`
`fs/volumes/clickhouse-02/etc/clickhouse-server/config.d`	`config.xml`

Each section of the above configuration file is explained in more detail below.

Networking and logging

External communication to the network interface is enabled by activating the listen host setting. This ensures that the ClickHouse server host is reachable by other hosts:

<listen_host>0.0.0.0</listen_host>

The port for the HTTP API is set to 8123:

<http_port>8123</http_port>

The TCP port for interaction by ClickHouse’s native protocol between clickhouse-client and other native ClickHouse tools, and clickhouse-server and other clickhouse-servers is set to 9000:

<tcp_port>9000</tcp_port>

Logging is defined in the <logger> block. This example configuration gives you a debug log that will roll over at 1000M three times:

<logger>
    <level>debug</level>
    <log>/var/log/clickhouse-server/clickhouse-server.log</log>
    <errorlog>/var/log/clickhouse-server/clickhouse-server.err.log</errorlog>
    <size>1000M</size>
    <count>3</count>
</logger>

For more information on logging configuration, see the comments included in the default ClickHouse configuration file.

Cluster configuration

Configuration for the cluster is set up in the <remote_servers> block. Here the cluster name cluster_1S_2R is defined.The <cluster_1S_2R></cluster_1S_2R> block defines the layout of the cluster, using the <shard></shard> and <replica></replica> settings, and acts as a template for distributed DDL queries, which are queries that execute across the cluster using the ON CLUSTER clause. By default, distributed DDL queries are allowed, but can also be turned off with setting allow_distributed_ddl_queries.internal_replication is set to true so that data is written to just one of the replicas.

<remote_servers>
    <!-- cluster name (should not contain dots) -->
    <cluster_1S_2R>
        <!-- <allow_distributed_ddl_queries>false</allow_distributed_ddl_queries> -->
        <shard>
            <!-- Optional. Whether to write data to just one of the replicas. Default: false (write data to all replicas). -->
            <internal_replication>true</internal_replication>
            <replica>
                <host>clickhouse-01</host>
                <port>9000</port>
            </replica>
            <replica>
                <host>clickhouse-02</host>
                <port>9000</port>
            </replica>
        </shard>
    </cluster_1S_2R>
</remote_servers>

For each server, the following parameters are specified:

Parameter	Description	Default Value
`host`	The address of the remote server. You can use either the domain or the IPv4 or IPv6 address. If you specify the domain, the server makes a DNS request when it starts, and the result is stored as long as the server is running. If the DNS request fails, the server doesn’t start. If you change the DNS record, you need to restart the server.	-
`port`	The TCP port for messenger activity (`tcp_port` in the config, usually set to 9000). Not to be confused with `http_port`.	-

Keeper configuration

The <ZooKeeper> section tells ClickHouse where ClickHouse Keeper (or ZooKeeper) is running. As we’re using a ClickHouse Keeper cluster, each <node> of the cluster needs to be specified, along with its hostname and port number using the <host> and <port> tags respectively.Set up of ClickHouse Keeper is explained in the next step of the tutorial.

<zookeeper>
    <node>
        <host>clickhouse-keeper-01</host>
        <port>9181</port>
    </node>
    <node>
        <host>clickhouse-keeper-02</host>
        <port>9181</port>
    </node>
    <node>
        <host>clickhouse-keeper-03</host>
        <port>9181</port>
    </node>
</zookeeper>

Although it is possible to run ClickHouse Keeper on the same server as ClickHouse Server, in production environments we strongly recommend that ClickHouse Keeper runs on dedicated hosts.

Macros configuration

Additionally, the <macros> section is used to define parameter substitutions for replicated tables. These are listed in system.macros and allow using substitutions like {shard} and {replica} in queries.

<macros>
    <shard>01</shard>
    <replica>01</replica>
    <cluster>cluster_1S_2R</cluster>
</macros>

These will be defined uniquely depending on the layout of the cluster.

User configuration

Now modify each empty configuration file users.xml located at fs/volumes/clickhouse-{}/etc/clickhouse-server/users.d with the following:

/users.d/users.xml

<?xml version="1.0"?>
<clickhouse replace="true">
    <profiles>
        <default>
            <max_memory_usage>10000000000</max_memory_usage>
            <use_uncompressed_cache>0</use_uncompressed_cache>
            <load_balancing>in_order</load_balancing>
            <log_queries>1</log_queries>
        </default>
    </profiles>
    <users>
        <default>
            <access_management>1</access_management>
            <profile>default</profile>
            <networks>
                <ip>::/0</ip>
            </networks>
            <quota>default</quota>
            <access_management>1</access_management>
            <named_collection_control>1</named_collection_control>
            <show_named_collections>1</show_named_collections>
            <show_named_collections_secrets>1</show_named_collections_secrets>
        </default>
    </users>
    <quotas>
        <default>
            <interval>
                <duration>3600</duration>
                <queries>0</queries>
                <errors>0</errors>
                <result_rows>0</result_rows>
                <read_rows>0</read_rows>
                <execution_time>0</execution_time>
            </interval>
        </default>
    </quotas>
</clickhouse>

Directory	File
`fs/volumes/clickhouse-01/etc/clickhouse-server/users.d`	`users.xml`
`fs/volumes/clickhouse-02/etc/clickhouse-server/users.d`	`users.xml`

In this example, the default user is configured without a password for simplicity. In practice, this is discouraged.

In this example, each users.xml file is identical for all nodes in the cluster.

Configure ClickHouse Keeper

Keeper setup

In order for replication to work, a ClickHouse keeper cluster needs to be set up and configured. ClickHouse Keeper provides the coordination system for data replication, acting as a stand in replacement for Zookeeper, which could also be used. ClickHouse Keeper is, however, recommended, as it provides better guarantees and reliability and uses fewer resources than ZooKeeper. For high availability and to keep quorum, it is recommended to run at least three ClickHouse Keeper nodes.

ClickHouse Keeper can run on any node of the cluster alongside ClickHouse, although it is recommended to have it run on a dedicated node which allows scaling and managing the ClickHouse Keeper cluster independently of the database cluster.

Create the keeper_config.xml files for each ClickHouse Keeper node using the following command from the root of the example folder:

for i in {01..03}; do
  touch fs/volumes/clickhouse-keeper-${i}/etc/clickhouse-keeper/keeper_config.xml
done

Modify the empty configuration files which were created in each node directory fs/volumes/clickhouse-keeper-{}/etc/clickhouse-keeper. The highlighted lines below need to be changed to be specific to each node:

/clickhouse-keeper/keeper_config.xml

<clickhouse replace="true">
    <logger>
        <level>information</level>
        <log>/var/log/clickhouse-keeper/clickhouse-keeper.log</log>
        <errorlog>/var/log/clickhouse-keeper/clickhouse-keeper.err.log</errorlog>
        <size>1000M</size>
        <count>3</count>
    </logger>
    <listen_host>0.0.0.0</listen_host>
    <keeper_server>
        <tcp_port>9181</tcp_port>
        <!--highlight-next-line-->
        <server_id>1</server_id>
        <log_storage_path>/var/lib/clickhouse/coordination/log</log_storage_path>
        <snapshot_storage_path>/var/lib/clickhouse/coordination/snapshots</snapshot_storage_path>
        <coordination_settings>
            <operation_timeout_ms>10000</operation_timeout_ms>
            <session_timeout_ms>30000</session_timeout_ms>
            <raft_logs_level>information</raft_logs_level>
        </coordination_settings>
        <raft_configuration>
            <server>
                <id>1</id>
                <hostname>clickhouse-keeper-01</hostname>
                <port>9234</port>
            </server>
            <server>
                <id>2</id>
                <hostname>clickhouse-keeper-02</hostname>
                <port>9234</port>
            </server>
            <server>
                <id>3</id>
                <hostname>clickhouse-keeper-03</hostname>
                <port>9234</port>
            </server>
        </raft_configuration>
    </keeper_server>
</clickhouse>

Directory	File
`fs/volumes/clickhouse-keeper-01/etc/clickhouse-keeper`	`keeper_config.xml`
`fs/volumes/clickhouse-keeper-02/etc/clickhouse-keeper`	`keeper_config.xml`
`fs/volumes/clickhouse-keeper-03/etc/clickhouse-keeper`	`keeper_config.xml`

Each configuration file will contain the following unique configuration (shown below). The server_id used should be unique for that particular ClickHouse Keeper node in the cluster and match the server <id> defined in the <raft_configuration> section. tcp_port is the port used by clients of ClickHouse Keeper.

<tcp_port>9181</tcp_port>
<server_id>{id}</server_id>

The following section is used to configure the servers that participate in the quorum for the raft consensus algorithm:

<raft_configuration>
    <server>
        <id>1</id>
        <hostname>clickhouse-keeper-01</hostname>
        <!-- TCP port used for communication between ClickHouse Keeper nodes -->
        <!--highlight-next-line-->
        <port>9234</port>
    </server>
    <server>
        <id>2</id>
        <hostname>clickhouse-keeper-02</hostname>
        <port>9234</port>
    </server>
    <server>
        <id>3</id>
        <hostname>clickhouse-keeper-03</hostname>
        <port>9234</port>
    </server>
</raft_configuration>

ClickHouse Cloud simplifies managementClickHouse Cloud removes the operational burden associated with managing shards and replicas. The platform automatically handles high availability, replication, and scaling decisions. Compute and storage are separate and scale based on demand without requiring manual configuration or ongoing maintenance.Read more

Test the setup

Make sure that docker is running on your machine. Start the cluster using the docker-compose up command from the root of the cluster_1S_2R directory:

docker-compose up -d

You should see docker begin to pull the ClickHouse and Keeper images, and then start the containers:

[+] Running 6/6
 ✔ Network cluster_1s_2r_default   Created
 ✔ Container clickhouse-keeper-03  Started
 ✔ Container clickhouse-keeper-02  Started
 ✔ Container clickhouse-keeper-01  Started
 ✔ Container clickhouse-01         Started
 ✔ Container clickhouse-02         Started

To verify that the cluster is running, connect to either clickhouse-01 or clickhouse-02 and run the following query. The command to connect to the first node is shown:

# Connect to any node
docker exec -it clickhouse-01 clickhouse-client

If successful, you will see the ClickHouse client prompt:

cluster_1S_2R node 1 :)

Run the following query to check what cluster topologies are defined for which hosts:

Query

SELECT 
    cluster,
    shard_num,
    replica_num,
    host_name,
    port
FROM system.clusters;

Response

   ┌─cluster───────┬─shard_num─┬─replica_num─┬─host_name─────┬─port─┐
1. │ cluster_1S_2R │         1 │           1 │ clickhouse-01 │ 9000 │
2. │ cluster_1S_2R │         1 │           2 │ clickhouse-02 │ 9000 │
3. │ default       │         1 │           1 │ localhost     │ 9000 │
   └───────────────┴───────────┴─────────────┴───────────────┴──────┘

Run the following query to check the status of the ClickHouse Keeper cluster:

Query

SELECT *
FROM system.zookeeper
WHERE path IN ('/', '/clickhouse')

Response

   ┌─name───────┬─value─┬─path────────┐
1. │ sessions   │       │ /clickhouse │
2. │ task_queue │       │ /clickhouse │
3. │ keeper     │       │ /           │
4. │ clickhouse │       │ /           │
   └────────────┴───────┴─────────────┘

The mntr command is also commonly used to verify that ClickHouse Keeper is running and to get state information about the relationship of the three Keeper nodes. In the configuration used in this example, there are three nodes working together. The nodes will elect a leader, and the remaining nodes will be followers.The mntr command gives information related to performance, and whether a particular node is a follower or a leader.

You may need to install netcat in order to send the mntr command to Keeper. Please see the nmap.org page for download information.

Run the command below from a shell on clickhouse-keeper-01, clickhouse-keeper-02, and clickhouse-keeper-03 to check the status of each Keeper node. The command for clickhouse-keeper-01 is shown below:

docker exec -it clickhouse-keeper-01  /bin/sh -c 'echo mntr | nc 127.0.0.1 9181'

The response below shows an example response from a follower node:

Response

zk_version      v23.3.1.2823-testing-46e85357ce2da2a99f56ee83a079e892d7ec3726
zk_avg_latency  0
zk_max_latency  0
zk_min_latency  0
zk_packets_received     0
zk_packets_sent 0
zk_num_alive_connections        0
zk_outstanding_requests 0
# highlight-next-line
zk_server_state follower
zk_znode_count  6
zk_watch_count  0
zk_ephemerals_count     0
zk_approximate_data_size        1271
zk_key_arena_size       4096
zk_latest_snapshot_size 0
zk_open_file_descriptor_count   46
zk_max_file_descriptor_count    18446744073709551615

The response below shows an example response from a leader node:

Response

zk_version      v23.3.1.2823-testing-46e85357ce2da2a99f56ee83a079e892d7ec3726
zk_avg_latency  0
zk_max_latency  0
zk_min_latency  0
zk_packets_received     0
zk_packets_sent 0
zk_num_alive_connections        0
zk_outstanding_requests 0
# highlight-next-line
zk_server_state leader
zk_znode_count  6
zk_watch_count  0
zk_ephemerals_count     0
zk_approximate_data_size        1271
zk_key_arena_size       4096
zk_latest_snapshot_size 0
zk_open_file_descriptor_count   48
zk_max_file_descriptor_count    18446744073709551615
# highlight-start
zk_followers    2
zk_synced_followers     2
# highlight-end

With this, you have successfully set up a ClickHouse cluster with a single shard and two replicas. In the next step, you will create a table in the cluster.

Create a database

Now that you have verified the cluster is correctly setup and is running, you will be recreating the same table as the one used in the UK property prices example dataset tutorial. It consists of around 30 million rows of prices paid for real-estate property in England and Wales since 1995.Connect to the client of each host by running each of the following commands from separate terminal tabs or windows:

docker exec -it clickhouse-01 clickhouse-client
docker exec -it clickhouse-02 clickhouse-client

You can run the query below from clickhouse-client of each host to confirm that there are no databases created yet, apart from the default ones:

Query

SHOW DATABASES;

Response

   ┌─name───────────────┐
1. │ INFORMATION_SCHEMA │
2. │ default            │
3. │ information_schema │
4. │ system             │
   └────────────────────┘

From the clickhouse-01 client run the following distributed DDL query using the ON CLUSTER clause to create a new database called uk:

CREATE DATABASE IF NOT EXISTS uk 
-- highlight-next-line
ON CLUSTER cluster_1S_2R;

You can again run the same query as before from the client of each host to confirm that the database has been created across the cluster despite running the query only clickhouse-01:

SHOW DATABASES;

   ┌─name───────────────┐
1. │ INFORMATION_SCHEMA │
2. │ default            │
3. │ information_schema │
4. │ system             │
#highlight-next-line
5. │ uk                 │
   └────────────────────┘

Create a table on the cluster

Now that the database has been created, create a table on the cluster. Run the following query from any of the host clients:

CREATE TABLE IF NOT EXISTS uk.uk_price_paid_local
--highlight-next-line
ON CLUSTER cluster_1S_2R
(
    price UInt32,
    date Date,
    postcode1 LowCardinality(String),
    postcode2 LowCardinality(String),
    type Enum8('terraced' = 1, 'semi-detached' = 2, 'detached' = 3, 'flat' = 4, 'other' = 0),
    is_new UInt8,
    duration Enum8('freehold' = 1, 'leasehold' = 2, 'unknown' = 0),
    addr1 String,
    addr2 String,
    street LowCardinality(String),
    locality LowCardinality(String),
    town LowCardinality(String),
    district LowCardinality(String),
    county LowCardinality(String)
)
--highlight-next-line
ENGINE = ReplicatedMergeTree
ORDER BY (postcode1, postcode2, addr1, addr2);

Notice that it is identical to the query used in the original CREATE statement of the UK property prices example dataset tutorial, except for the ON CLUSTER clause and use of the ReplicatedMergeTree engine.The ON CLUSTER clause is designed for distributed execution of DDL (Data Definition Language) queries such as CREATE, DROP, ALTER, and RENAME, ensuring that these schema changes are applied across all nodes in a cluster.The ReplicatedMergeTree engine works just as the ordinary MergeTree table engine, but it will also replicate the data.You can run the query below from either clickhouse-01 or clickhouse-02 client to confirm that the table has been created across the cluster:

Query

SHOW TABLES IN uk;

Response

   ┌─name────────────────┐
1. │ uk_price_paid.      │
   └─────────────────────┘

Insert data

As the data set is large and takes a few minutes to completely ingest, we will insert only a small subset to begin with.Insert a smaller subset of the data using the query below from clickhouse-01:

INSERT INTO uk.uk_price_paid_local
SELECT
    toUInt32(price_string) AS price,
    parseDateTimeBestEffortUS(time) AS date,
    splitByChar(' ', postcode)[1] AS postcode1,
    splitByChar(' ', postcode)[2] AS postcode2,
    transform(a, ['T', 'S', 'D', 'F', 'O'], ['terraced', 'semi-detached', 'detached', 'flat', 'other']) AS type,
    b = 'Y' AS is_new,
    transform(c, ['F', 'L', 'U'], ['freehold', 'leasehold', 'unknown']) AS duration,
    addr1,
    addr2,
    street,
    locality,
    town,
    district,
    county
FROM url(
    'http://prod1.publicdata.landregistry.gov.uk.s3-website-eu-west-1.amazonaws.com/pp-complete.csv',
    'CSV',
    'uuid_string String,
    price_string String,
    time String,
    postcode String,
    a String,
    b String,
    c String,
    addr1 String,
    addr2 String,
    street String,
    locality String,
    town String,
    district String,
    county String,
    d String,
    e String'
) LIMIT 10000
SETTINGS max_http_get_redirects=10;

Notice that the data is completely replicated on each host:

-- clickhouse-01
SELECT count(*)
FROM uk.uk_price_paid_local

--   ┌─count()─┐
-- 1.│   10000 │
--   └─────────┘

-- clickhouse-02
SELECT count(*)
FROM uk.uk_price_paid_local

--   ┌─count()─┐
-- 1.│   10000 │
--   └─────────┘

To demonstrate what happens when one of the hosts fails, create a simple test database and test table from either of the hosts:

CREATE DATABASE IF NOT EXISTS test ON CLUSTER cluster_1S_2R;
CREATE TABLE test.test_table ON CLUSTER cluster_1S_2R
(
    `id` UInt64,
    `name` String
)
ENGINE = ReplicatedMergeTree
ORDER BY id;

As with the uk_price_paid table, we can insert data from either host:

INSERT INTO test.test_table (id, name) VALUES (1, 'Clicky McClickface');

But what will happen if one of the hosts is down? To simulate this, stop clickhouse-01 by running:

docker stop clickhouse-01

Check that the host is down by running:

docker-compose ps

Response

NAME                   IMAGE                                        COMMAND            SERVICE                CREATED          STATUS          PORTS
clickhouse-02          clickhouse/clickhouse-server:latest          "/entrypoint.sh"   clickhouse-02          X minutes ago    Up X minutes    127.0.0.1:8124->8123/tcp, 127.0.0.1:9001->9000/tcp
clickhouse-keeper-01   clickhouse/clickhouse-keeper:latest-alpine   "/entrypoint.sh"   clickhouse-keeper-01   X minutes ago    Up X minutes    127.0.0.1:9181->9181/tcp
clickhouse-keeper-02   clickhouse/clickhouse-keeper:latest-alpine   "/entrypoint.sh"   clickhouse-keeper-02   X minutes ago    Up X minutes    127.0.0.1:9182->9181/tcp
clickhouse-keeper-03   clickhouse/clickhouse-keeper:latest-alpine   "/entrypoint.sh"   clickhouse-keeper-03   X minutes ago    Up X minutes    127.0.0.1:9183->9181/tcp

With clickhouse-01 now down, insert another row of data into the test table and query the table:

INSERT INTO test.test_table (id, name) VALUES (2, 'Alexey Milovidov');
SELECT * FROM test.test_table;

Response

   ┌─id─┬─name───────────────┐
1. │  1 │ Clicky McClickface │
2. │  2 │ Alexey Milovidov   │
   └────┴────────────────────┘

Now restart clickhouse-01 with the following command (you can run docker-compose ps again after to confirm):

docker start clickhouse-01

Query the test table again from clickhouse-01 after running docker exec -it clickhouse-01 clickhouse-client:

Query

SELECT * FROM test.test_table

Response

   ┌─id─┬─name───────────────┐
1. │  1 │ Clicky McClickface │
2. │  2 │ Alexey Milovidov   │
   └────┴────────────────────┘

If at this stage you would like to ingest the full UK property price dataset to play around with, you can run the following queries to do so:

TRUNCATE TABLE uk.uk_price_paid_local ON CLUSTER cluster_1S_2R;
INSERT INTO uk.uk_price_paid_local
SELECT
    toUInt32(price_string) AS price,
    parseDateTimeBestEffortUS(time) AS date,
    splitByChar(' ', postcode)[1] AS postcode1,
    splitByChar(' ', postcode)[2] AS postcode2,
    transform(a, ['T', 'S', 'D', 'F', 'O'], ['terraced', 'semi-detached', 'detached', 'flat', 'other']) AS type,
    b = 'Y' AS is_new,
    transform(c, ['F', 'L', 'U'], ['freehold', 'leasehold', 'unknown']) AS duration,
    addr1,
    addr2,
    street,
    locality,
    town,
    district,
    county
FROM url(
    'http://prod1.publicdata.landregistry.gov.uk.s3-website-eu-west-1.amazonaws.com/pp-complete.csv',
    'CSV',
    'uuid_string String,
    price_string String,
    time String,
    postcode String,
    a String,
    b String,
    c String,
    addr1 String,
    addr2 String,
    street String,
    locality String,
    town String,
    district String,
    county String,
    d String,
    e String'
    ) SETTINGS max_http_get_redirects=10;

Query the table from clickhouse-02 or clickhouse-01:

Query

SELECT count(*) FROM uk.uk_price_paid_local;

Response

   ┌──count()─┐
1. │ 30212555 │ -- 30.21 million
   └──────────┘

Conclusion

The advantage of this cluster topology is that with two replicas, your data exists on two separate hosts. If one host fails, the other replica continues serving data without any loss. This eliminates single points of failure at the storage level. When one host goes down, the remaining replica is still able to:

Handle read queries without interruption
Accept new writes (depending on your consistency settings)
Maintain service availability for applications

When the failed host comes back online, it is able to:

Automatically sync missing data from the healthy replica
Resume normal operations without manual intervention
Restore full redundancy quickly

In the next example, we’ll look at how to set up a cluster with two shards but only one replica.

ClickHouse guides

Use case guides

Prerequisites

Set up directory structure and test environment

Configure ClickHouse nodes

Server setup

Networking and logging

Cluster configuration

Keeper configuration

Macros configuration

User configuration

Configure ClickHouse Keeper

Keeper setup

Test the setup

Create a database

Create a table on the cluster

Insert data

Conclusion

ClickHouse guides

Use case guides

Documentation Index

​Prerequisites

​Set up directory structure and test environment

​Configure ClickHouse nodes

​Server setup

​Networking and logging

​Cluster configuration

​Keeper configuration

​Macros configuration

​User configuration

​Configure ClickHouse Keeper

​Keeper setup

​Test the setup

​Create a database

​Create a table on the cluster

​Insert data

​Conclusion

Prerequisites

Set up directory structure and test environment

Configure ClickHouse nodes

Server setup

Networking and logging

Cluster configuration

Keeper configuration

Macros configuration

User configuration

Configure ClickHouse Keeper

Keeper setup

Test the setup

Create a database

Create a table on the cluster

Insert data

Conclusion