Relational Database Read-Side Support

§Relational Database Read-Side support

This page is specifically about Lagom’s support for relational database read-sides. Before reading this, you should familiarize yourself with Lagom’s general read-side support.

§Query the Read-Side Database

Let us first look at how a service implementation can retrieve data from a relational database.

import scala.collection.immutable
import scala.collection.immutable.VectorBuilder
import akka.NotUsed
import com.lightbend.lagom.scaladsl.api.Service
import com.lightbend.lagom.scaladsl.api.ServiceCall
import com.lightbend.lagom.scaladsl.persistence.jdbc.JdbcSession
class BlogServiceImpl(jdbcSession: JdbcSession) extends BlogService {
  import JdbcSession.tryWith

  override def getPostSummaries() = ServiceCall { request =>
    jdbcSession.withConnection { connection =>
      tryWith(connection.prepareStatement("SELECT id, title FROM blogsummary")) { ps =>
        tryWith(ps.executeQuery()) { rs =>
          val summaries = new VectorBuilder[PostSummary]
          while ( {
            summaries += PostSummary(rs.getString("id"), rs.getString("title"))

Note that the JdbcSession is injected in the constructor. JdbcSession allows access to a connection from the connection pool, using the withConnection method, and will manage transactions using the withTransaction method. Importantly, JdbcSession also manages execution of the blocking JDBC calls in a thread pool designed to handle it, which is why the withConnection and withTransaction methods return Future.

§Update the Read-Side

We need to transform the events generated by the Persistent Entities into database tables that can be queried as illustrated in the previous section. For that we will implement a ReadSideProcessor with assistance from the JdbcReadSide support component. It will consume events produced by persistent entities and update one or more database tables that are optimized for queries.

This is how a ReadSideProcessor class looks like before filling in the implementation details:

import com.lightbend.lagom.scaladsl.persistence.AggregateEventTag
import com.lightbend.lagom.scaladsl.persistence.ReadSideProcessor
import com.lightbend.lagom.scaladsl.persistence.jdbc.JdbcReadSide
import java.sql.Connection
import java.sql.PreparedStatement
import java.sql.SQLException
import com.lightbend.lagom.scaladsl.persistence.EventStreamElement
import scala.concurrent.ExecutionContext
import com.lightbend.lagom.scaladsl.persistence.jdbc.JdbcSession.tryWith
class BlogEventProcessor(readSide: JdbcReadSide)(implicit ec: ExecutionContext)
  extends ReadSideProcessor[BlogEvent] {

  override def buildHandler(): ReadSideProcessor.ReadSideHandler[BlogEvent] = {
    // TODO build read side handler

  override def aggregateTags: Set[AggregateEventTag[BlogEvent]] = {
    // TODO return the tag for the events

You can see that we have injected the JDBC read-side support, this will be needed later.

You should already have implemented tagging for your events as described in the Read-Side documentation, so first we’ll implement the aggregateTags method in our read-side processor stub, like so:

override def aggregateTags: Set[AggregateEventTag[BlogEvent]] =

§Building the read-side handler

The other method on the ReadSideProcessor is buildHandler. This is responsible for creating the ReadSideHandler that will handle events. It also gives the opportunity to run two callbacks, one is a global prepare callback, the other is a regular prepare callback.

JdbcReadSide has a builder method for creating a builder for these handlers, this builder will create a handler that will automatically manage transactions and handle read-side offsets for you. It can be created like so:

val builder = readSide.builder[BlogEvent]("blogsummaryoffset")

The argument passed to this method is an identifier for the read-side processor that Lagom should use when it persists the offset. Lagom will store the offsets in a table that it will automatically create itself if it doesn’t exist. If you would prefer that Lagom didn’t automatically create this table for you, you can turn off this feature by setting in application.conf. The DDL for the schema for this table is as follows:

CREATE TABLE read_side_offsets (
  read_side_id VARCHAR(255), tag VARCHAR(255),
  sequence_offset bigint, time_uuid_offset char(36),
  PRIMARY KEY (read_side_id, tag)

§Global prepare

The global prepare callback runs at least once across the whole cluster. It is intended for doing things like creating tables and preparing any data that needs to be available before read side processing starts. Read side processors may be sharded across many nodes, and so tasks like creating tables should usually only be done from one node.

The global prepare callback is run from an Akka cluster singleton. It may be run multiple times - every time a new node becomes the new singleton, the callback will be run. Consequently, the task must be idempotent. If it fails, it will be run again using an exponential backoff, and the read side processing of the whole cluster will not start until it has run successfully.

Of course, setting a global prepare callback is completely optional, you may prefer to manage database tables manually, but it is very convenient for development and test environments to use this callback to create them for you.

Below is an example method that we’ve implemented to create tables:

private def createTable(connection: Connection): Unit = {
  tryWith(connection.prepareStatement("CREATE TABLE IF NOT EXISTS blogsummary ( " +
    "id VARCHAR(64), title VARCHAR(256), PRIMARY KEY (id))")) { ps =>

It can then be registered as the global prepare callback in the buildHandler method:



In addition to the global prepare callback, there is also a prepare callback that can be specified by calling builder.setPrepare. This will be executed once per shard, when the read side processor starts up.

If you read the Cassandra read-side support guide, you may have seen this used to prepare database statements for later use. JDBC PreparedStatement instances, however, are not guaranteed to be thread-safe, so the prepare callback should not be used for this purpose with relational databases.

Again this callback is optional, and in our example we have no need for a prepare callback, so none is specified.

§Event handlers

The event handlers take an event and a connection, and update the read-side accordingly.

Here’s an example callback for handling the PostAdded event:

private def processPostAdded(connection: Connection,
  eventElement: EventStreamElement[PostAdded]): Unit = {
    "INSERT INTO blogsummary (id, title) VALUES (?, ?)")) { statement =>
    statement.setString(1, eventElement.event.postId)
    statement.setString(2, eventElement.event.content.title)

This can then be registered with the builder using setEventHandler:


Once you have finished registering all your event handlers, you can invoke the build method and return the built handler:

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