Follow-the-Workload

"Follow-the-workload" refers to CockroachDB's ability to dynamically optimize read latency for the location from which most of the workload is originating. This page explains how "follow-the-workload" works and walks you through a simple demonstration using a local cluster.

Overview

Basic terms

To understand how "follow-the-workload" works, it's important to start with some basic terms:

How it works

"Follow-the-workload" is based on the way range leases handle read requests. Read requests bypass the Raft consensus protocol, accessing the range replica that holds the range lease (the leaseholder) and sending the results to the client without needing to coordinate with any of the other range replicas. Bypassing Raft, and the network round trips involved, is possible because the leaseholder is guaranteed to be up-to-date due to the fact that all write requests also go to the leaseholder.

This increases the speed of reads, but it doesn't guarantee that the range lease will be anywhere close to the origin of requests. If requests are coming from the US West, for example, and the relevant range lease is on a node in the US East, the requests would likely enter a gateway node in the US West and then get routed to the node with the range lease in the US East.

However, you can cause the cluster to actively move range leases for even better read performance by starting each node with the —locality flag. With this flag specified, the cluster knows about the location of each node, so when there's high latency between nodes, the cluster will move active range leases to a node closer to the origin of the majority of the workload. This is especially helpful for applications with workloads that move around throughout the day (e.g., most of the traffic is in the US East in the morning and in the US West in the evening).

Tip:
To enable "follow-the-workload", you just need to start each node of the cluster with the —locality flag, as shown in the tutorial below. No additional user action is required.

Example

In this example, let's imagine that lots of read requests are going to node 1, and that the requests are for data in range 3. Because range 3's lease is on node 3, the requests are routed to node 3, which returns the results to node 1. Node 1 then responds to the clients.

However, if the nodes were started with the —locality flag, after a short while, the cluster would move range 3's lease to node 1, which is closer to the origin of the workload, thus reducing the network round trips and increasing the speed of reads.

Tutorial

Step 1. Install prerequisites

In this tutorial, you'll use CockroachDB, the comcast network tool to simulate network latency on your local workstation, and the tpcc workload built into CockroachDB to simulate client workloads. Before you begin, make sure these applications are installed:

• Install the latest version of CockroachDB.
• Install Go version 1.9 or higher. If you're on a Mac and using Homebrew, use brew install go. You can check your local version by running go version.
• Install the comcast network simulation tool: go get github.com/tylertreat/comcast
  Also, to keep track of the data files and logs for your cluster, you may want to create a new directory (e.g., mkdir follow-workload) and start all your nodes in that directory.

Step 2. Start simulating network latency

"Follow-the-workload" only kicks in when there's high latency between the nodes of the CockroachDB cluster. In this tutorial, you'll run 3 nodes on your local workstation, with each node pretending to be in a different region of the US. To simulate latency between the nodes, use the comcast tool that you installed earlier.

In a new terminal, start comcast as follows:

$ comcast --device lo0 --latency 100

For the —device flag, use lo0 if you're on Mac or lo if you're on Linux. If neither works, run the ifconfig command and find the interface responsible for 127.0.0.1 in the output.

This command causes a 100 millisecond delay for all requests on the loopback interface of your local workstation. It will only affect connections from the machine to itself, not to/from the Internet.

Step 3. Start the cluster

Use the cockroach start command to start 3 nodes on your local workstation, using the —locality flag to pretend that each node is in a different region of the US.

• In a new terminal, start a node in the "US West":

$ cockroach start \
--insecure \
--locality=region=us-west \
--store=follow1 \
--listen-addr=localhost:26257 \
--http-addr=localhost:8080 \
--join=localhost:26257,localhost:26258,localhost:26259

• In a new terminal, start a node in the "US Midwest":

$ cockroach start \
--insecure \
--locality=region=us-midwest \
--store=follow2 \
--listen-addr=localhost:26258 \
--http-addr=localhost:8081 \
--join=localhost:26257,localhost:26258,localhost:26259

• In a new terminal, start a node in the "US East":

$ cockroach start \
--insecure \
--locality=region=us-east \
--store=follow3 \
--listen-addr=localhost:26259 \
--http-addr=localhost:8082 \
--join=localhost:26257,localhost:26258,localhost:26259

Step 4. Initialize the cluster

In a new terminal, use the cockroach init command to perform a one-time initialization of the cluster:

$ cockroach init \
--insecure \
--host=localhost:26257

Step 5. Simulate traffic in the US East

Now that the cluster is live, use the tpcc workload to simulate multiple client connections to the node in the "US East".

• In the same terminal, run the cockroach workload init tpcc command to load the initial schema and data, pointing it at port 26259, which is the port of the node with the us-east locality:

$ cockroach workload init tpcc \
'postgresql://root@localhost:26259?sslmode=disable'

• Let the workload run to completion.

Step 6. Check the location of the range lease

The load generator created a tpcc database with several tables that map to underlying key-value ranges. Verify that the range lease for the customer table moved to the node in the "US East" as follows.

• In the same terminal, run the cockroach node status command against any node:

$ cockroach node status --insecure --host=localhost:26259

  id |     address     |                 build                  |            started_at            |            updated_at            | is_available | is_live
+----+-----------------+----------------------------------------+----------------------------------+----------------------------------+--------------+---------+
   1 | localhost:26257 | v2.2.0-alpha.00000000-2397-geb8345b19c | 2018-11-21 03:12:17.572557+00:00 | 2018-11-21 03:16:11.917193+00:00 | true         | true
   2 | localhost:26259 | v2.2.0-alpha.00000000-2397-geb8345b19c | 2018-11-21 03:12:18.935464+00:00 | 2018-11-21 03:16:13.510253+00:00 | true         | true
   3 | localhost:26258 | v2.2.0-alpha.00000000-2397-geb8345b19c | 2018-11-21 03:12:19.11294+00:00  | 2018-11-21 03:16:13.571382+00:00 | true         | true
(3 rows)

• In the response, note the ID of the node running on port 26259 (in this case, node 2).

• In the same terminal, connect the built-in SQL shell to any node:

$ cockroach sql --insecure --host=localhost:26259

• Check where the range lease is for the tpcc.customer table:

> SHOW EXPERIMENTAL_RANGES FROM TABLE tpcc.customer;

  start_key | end_key | range_id | replicas | lease_holder
+-----------+---------+----------+----------+--------------+
  NULL      | NULL    |       33 | {1,2,3}  |            2
(1 row)

replicas and lease_holder indicate the node IDs. As you can see, the lease for the range holding the customer table's data is on node 2, which is the same ID as the node on port 26259.

• Exit the SQL shell:

> \q

Step 7. Simulate traffic in the US West

• In the same terminal, run the cockroach workload run tpcc command to generate more load, this time pointing it at port 26257, which is the port of the node with the us-west locality:

$ cockroach workload run tpcc \
--duration=5m \
'postgresql://root@localhost:26257?sslmode=disable'

You'll see per-operation statistics print to standard output every second.

• Let the workload run to completion. This is necessary since the system will still "remember" the earlier requests to the other locality.

Note:

The latency numbers printed by the workload will be over 200 milliseconds because the 100 millisecond delay in each direction (200ms round-trip) caused by the comcast tool also applies to the traffic going from the tpcc process to the cockroach process. If you were to set up more advanced rules that excluded the tpcc process's traffic or to run this on a real network with real network delay, these numbers would be down in the single-digit milliseconds.

Step 8. Check the location of the range lease

Verify that the range lease for the customer table moved to the node in the "US West" as follows.

• Connect the built-in SQL shell to any node:

$ cockroach sql --insecure --host=localhost:26257

• Check where the range lease is for the kv table:

> SHOW EXPERIMENTAL_RANGES FROM TABLE test.kv;

  start_key | end_key | range_id | replicas | lease_holder
+-----------+---------+----------+----------+--------------+
  NULL      | NULL    |       33 | {1,2,3}  |            1
(1 row)

As you can see, the lease for the range holding the customer table's data is now on node 1, which is the same ID as the node on port 26257.

Step 9. Stop the cluster

Once you're done with your cluster, press CTRL-C in each node's terminal.

Tip:

For the last node, the shutdown process will take longer (about a minute) and will eventually force kill the node. This is because, with only 1 node still online, a majority of replicas are no longer available (2 of 3), and so the cluster is not operational. To speed up the process, press CTRL-C a second time.

If you do not plan to restart the cluster, you may want to remove the nodes' data stores:

$ rm -rf follow1 follow2 follow3

Step 10. Stop simulating network latency

Once you're done with this tutorial, you will not want a 100 millisecond delay for all requests on your local workstation, so stop the comcast tool:

$ comcast --device lo0 --stop

What's next?

Explore other core CockroachDB benefits and features:

• Data Replication
• Fault Tolerance & Recovery
• Automatic Rebalancing
• Serializable Transactions
• Cross-Cloud Migration
• Follow-the-Workload
• Orchestration
• JSON Support

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