Prerequisite

Install a local YugabyteDB universe on Docker using the steps below.

mkdir ~/yugabyte && cd ~/yugabyte
wget https://raw.githubusercontent.com/yugabyte/yugabyte-db/master/bin/yb-docker-ctl && chmod +x yb-docker-ctl
docker pull yugabytedb/yugabyte

1. Create universe

If you have a previously running local universe, destroy it using the following.

$ ./yb-docker-ctl destroy

Start a new local universe with a replication factor (RF) of 5. This will create five nodes.

$ ./yb-docker-ctl create --rf 5 

Add two more nodes.

$ ./yb-docker-ctl add_node

$ ./yb-docker-ctl add_node

2. Write some data

Pull the yb-sample-apps Docker container. This container has built-in Java client programs for various workloads, including SQL inserts and updates.

$ docker pull yugabytedb/yb-sample-apps

By default, the key-value workload application runs with strong read consistency where all data is read from the tablet leader. We are going to populate exactly one key with a 10KB value into the system. Since the replication factor is 5, this key will get replicated to five of the seven nodes in the universe.

Run the CassandraKeyValue workload application to constantly update this key-value, as well as perform reads with strong consistency against the local universe.

$ docker run --name yb-sample-apps --hostname yb-sample-apps --net yb-net yugabytedb/yb-sample-apps --workload CassandraKeyValue \
  --nodes yb-tserver-n1:9042 \
  --nouuid \
  --num_unique_keys 1 \
  --num_threads_write 1 \
  --num_threads_read 1 \
  --value_size 10240

In the above command, we have set the value of num_unique_keys to 1, which means we are overwriting a single key key:0. We can verify this using ycqlsh:

$ docker exec -it yb-tserver-n1 /home/yugabyte/bin/ycqlsh

Connected to local cluster at localhost:9042.
[ycqlsh 5.0.1 | Cassandra 3.9-SNAPSHOT | CQL spec 3.4.2 | Native protocol v4]
Use HELP for help.

ycqlsh> SELECT k FROM ybdemo_keyspace.cassandrakeyvalue;

 k
-------
 key:0

(1 rows)

3. Strongly consistent reads from tablet leaders

When performing strongly consistent reads as a part of the above command, all reads will be served by the tablet leader of the tablet that contains the key key:0. If we browse to the tablet-servers page, we will see that all the requests are indeed being served by one tserver:

4. Timeline consistent reads from tablet replicas

Let us stop the above sample app, and run the following variant of the sample app. This command will do updates to the same key key:0 which will go through the tablet leader, but it will reads from the replicas.

$ java -jar ./yb-sample-apps.jar --workload CassandraKeyValue \
                                    --nodes localhost:9042 \
                                    --nouuid \
                                    --num_unique_keys 1 \
                                    --num_threads_write 1 \
                                    --num_threads_read 1 \
                                    --value_size 10240 \
                                    --local_reads

This can be easily seen by refreshing the tablet-servers page, where we will see that the writes are served by a single YB-TServer that is the leader of the tablet for the key key:0 while multiple YB-TServers which are replicas serve the reads.

5. Clean up (optional)

Optionally, you can shutdown the local cluster created in Step 1.

$ ./yb-docker-ctl destroy