185 lines
8.3 KiB
Plaintext
185 lines
8.3 KiB
Plaintext
---
|
|
tags: []
|
|
projects: [spring-batch]
|
|
---
|
|
:spring_version: current
|
|
:spring_boot_version: 1.3.2.RELEASE
|
|
:Component: http://docs.spring.io/spring/docs/{spring_version}/javadoc-api/org/springframework/stereotype/Component.html
|
|
:SpringApplication: http://docs.spring.io/spring-boot/docs/{spring_boot_version}/api/org/springframework/boot/SpringApplication.html
|
|
:toc:
|
|
:icons: font
|
|
:source-highlighter: prettify
|
|
:project_id: gs-batch-processing
|
|
This guide walks you through the process of creating a basic batch-driven solution.
|
|
|
|
== What you'll build
|
|
|
|
You'll build a service that imports data from a CSV spreadsheet, transforms it with custom code, and stores the final results in a database.
|
|
|
|
|
|
== What you'll need
|
|
|
|
:java_version: 1.8
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/prereq_editor_jdk_buildtools.adoc[]
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/how_to_complete_this_guide.adoc[]
|
|
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/hide-show-gradle.adoc[]
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/hide-show-maven.adoc[]
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/hide-show-sts.adoc[]
|
|
|
|
== Business Data
|
|
|
|
Typically your customer or a business analyst supplies a spreadsheet. In this case, you make it up.
|
|
|
|
`src/main/resources/sample-data.csv`
|
|
[source,csv]
|
|
----
|
|
include::initial/src/main/resources/sample-data.csv[]
|
|
----
|
|
|
|
This spreadsheet contains a first name and a last name on each row, separated by a comma. This is a fairly common pattern that Spring handles out-of-the-box, as you will see.
|
|
|
|
|
|
Next, you write a SQL script to create a table to store the data.
|
|
|
|
`src/main/resources/schema-all.sql`
|
|
[source,sql]
|
|
----
|
|
include::initial/src/main/resources/schema-all.sql[]
|
|
----
|
|
|
|
NOTE: Spring Boot runs `schema-@@platform@@.sql` automatically during startup. `-all` is the default for all platforms.
|
|
|
|
|
|
[[initial]]
|
|
== Create a business class
|
|
|
|
Now that you see the format of data inputs and outputs, you write code to represent a row of data.
|
|
|
|
`src/main/java/hello/Person.java`
|
|
[source,java]
|
|
----
|
|
include::complete/src/main/java/hello/Person.java[]
|
|
----
|
|
|
|
You can instantiate the `Person` class either with first and last name through a constructor, or by setting the properties.
|
|
|
|
|
|
== Create an intermediate processor
|
|
|
|
A common paradigm in batch processing is to ingest data, transform it, and then pipe it out somewhere else. Here you write a simple transformer that converts the names to uppercase.
|
|
|
|
`src/main/java/hello/PersonItemProcessor.java`
|
|
[source,java]
|
|
----
|
|
include::complete/src/main/java/hello/PersonItemProcessor.java[]
|
|
----
|
|
|
|
`PersonItemProcessor` implements Spring Batch's `ItemProcessor` interface. This makes it easy to wire the code into a batch job that you define further down in this guide. According to the interface, you receive an incoming `Person` object, after which you transform it to an upper-cased `Person`.
|
|
|
|
NOTE: There is no requirement that the input and output types be the same. In fact, after one source of data is read, sometimes the application's data flow needs a different data type.
|
|
|
|
|
|
== Put together a batch job
|
|
|
|
Now you put together the actual batch job. Spring Batch provides many utility classes that reduce the need to write custom code. Instead, you can focus on the business logic.
|
|
|
|
`src/main/java/hello/BatchConfiguration.java`
|
|
[source,java]
|
|
----
|
|
include::complete/src/main/java/hello/BatchConfiguration.java[]
|
|
----
|
|
|
|
For starters, the `@EnableBatchProcessing` annotation adds many critical beans that support jobs and saves you a lot of leg work. This example uses a memory-based database (provided by `@EnableBatchProcessing`), meaning that when it's done, the data is gone.
|
|
|
|
Break it down:
|
|
|
|
`src/main/java/hello/BatchConfiguration.java`
|
|
[source,java]
|
|
----
|
|
include::/complete/src/main/java/hello/BatchConfiguration.java[tag=readerwriterprocessor]
|
|
----
|
|
.
|
|
The first chunk of code defines the input, processor, and output.
|
|
- `reader()` creates an `ItemReader`. It looks for a file called `sample-data.csv` and parses each line item with enough information to turn it into a `Person`.
|
|
- `processor()` creates an instance of our `PersonItemProcessor` you defined earlier, meant to uppercase the data.
|
|
- `write(DataSource)` creates an `ItemWriter`. This one is aimed at a JDBC destination and automatically gets a copy of the dataSource created by `@EnableBatchProcessing`. It includes the SQL statement needed to insert a single `Person` driven by Java bean properties.
|
|
|
|
The next chunk focuses on the actual job configuration.
|
|
|
|
`src/main/java/hello/BatchConfiguration.java`
|
|
[source,java]
|
|
----
|
|
include::/complete/src/main/java/hello/BatchConfiguration.java[tag=jobstep]
|
|
----
|
|
.
|
|
The first method defines the job and the second one defines a single step. Jobs are built from steps, where each step can involve a reader, a processor, and a writer.
|
|
|
|
In this job definition, you need an incrementer because jobs use a database to maintain execution state. You then list each step, of which this job has only one step. The job ends, and the Java API produces a perfectly configured job.
|
|
|
|
The `listener()` method lets you hook into the engine and detect when the job is complete, triggering the verification of results.
|
|
|
|
In the step definition, you define how much data to write at a time. In this case, it writes up to ten records at a time. Next, you configure the reader, processor, and writer using the injected bits from earlier.
|
|
|
|
NOTE: chunk() is prefixed `<Person,Person>` because it's a generic method. This represents the input and output types of each "chunk" of processing, and lines up with `ItemReader<Person>` and `ItemWriter<Person>`.
|
|
|
|
`src/main/java/hello/JobCompletionNotificationListener.java`
|
|
[source,java]
|
|
----
|
|
include::/complete/src/main/java/hello/JobCompletionNotificationListener.java[]
|
|
----
|
|
|
|
This code listens for when a job is `BatchStatus.COMPLETED`, and then uses `JdbcTemplate` to inspect the results.
|
|
|
|
|
|
== Make the application executable
|
|
|
|
Although batch processing can be embedded in web apps and WAR files, the simpler approach demonstrated below creates a standalone application. You package everything in a single, executable JAR file, driven by a good old Java `main()` method.
|
|
|
|
|
|
`src/main/java/hello/Application.java`
|
|
[source,java]
|
|
----
|
|
include::complete/src/main/java/hello/Application.java[]
|
|
----
|
|
|
|
`@SpringBootApplication` is a convenience annotation that adds all of the following:
|
|
|
|
- `@Configuration` tags the class as a source of bean definitions for the application context.
|
|
- `@EnableAutoConfiguration` tells Spring Boot to start adding beans based on classpath settings, other beans, and various property settings.
|
|
- `@ComponentScan` tells Spring to look for other components, configurations, and services in the the `hello` package allowing it to find the batch details.
|
|
|
|
For demonstration purposes, there is code to create a `JdbcTemplate`, query the database, and print out the names of people the batch job inserts.
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/build_an_executable_jar_subhead.adoc[]
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/build_an_executable_jar_with_both.adoc[]
|
|
|
|
The job prints out a line for each person that gets transformed. After the job runs, you can also see the output from querying the database.
|
|
|
|
....
|
|
Converting (firstName: Jill, lastName: Doe) into (firstName: JILL, lastName: DOE)
|
|
Converting (firstName: Joe, lastName: Doe) into (firstName: JOE, lastName: DOE)
|
|
Converting (firstName: Justin, lastName: Doe) into (firstName: JUSTIN, lastName: DOE)
|
|
Converting (firstName: Jane, lastName: Doe) into (firstName: JANE, lastName: DOE)
|
|
Converting (firstName: John, lastName: Doe) into (firstName: JOHN, lastName: DOE)
|
|
Found <firstName: JILL, lastName: DOE> in the database.
|
|
Found <firstName: JOE, lastName: DOE> in the database.
|
|
Found <firstName: JUSTIN, lastName: DOE> in the database.
|
|
Found <firstName: JANE, lastName: DOE> in the database.
|
|
Found <firstName: JOHN, lastName: DOE> in the database.
|
|
....
|
|
|
|
|
|
== Summary
|
|
|
|
Congratulations! You built a batch job that ingested data from a spreadsheet, processed it, and wrote it to a database.
|
|
|
|
|
|
include::https://raw.githubusercontent.com/spring-guides/getting-started-macros/master/footer.adoc[]
|
|
|