diff --git a/README.src.md b/README.src.md deleted file mode 100644 index 5824fe8217..0000000000 --- a/README.src.md +++ /dev/null @@ -1,134 +0,0 @@ -# Getting Started: Creating a Batch Service - -What you'll build ------------------ - -This guide walks you through creating a basic batch-driven solution. You 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 ----------------- - - - About 15 minutes - - {!include#prereq-editor-jdk-buildtools} - -## {!include#how-to-complete-this-guide} - - -Set up the project ------------------- -{!include#build-system-intro} - -{!include#create-directory-structure-hello} - -### Create a Maven POM - - {!include:initial/pom.xml} - -{!include#bootstrap-starter-pom-disclaimer} - -### Create 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` -```text -Jill,Doe -Joe,Doe -Justin,Doe -Jane,Doe -John,Doe -``` - -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. - -### Define the destination for your data - -Next, you write a SQL script to create a table to store the data. - - {!include:complete/src/main/resources/schema.sql} - - -Create a business class ------------------------ - -Now that you see the format of data inputs and outputs, you write code to represent a row of data. - - {!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. - - {!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. - - {!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. - -Break it down: - - {!include:complete/src/main/java/hello/BatchConfiguration.java#reader-writer-processor} - -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. - - {!include:complete/src/main/java/hello/BatchConfiguration.java#job-step} - -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. - -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 `` because it's a generic method. This represents the input and output types of each "chunk" of processing, and lines up with `ItemReader` and `ItemWriter`. - -Finally, you run the application. - - {!include:complete/src/main/java/hello/BatchConfiguration.java#template-main} - -This example uses a memory-based database (provided by `@EnableBatchProcessing`), meaning that when it's done, the data is gone. For demonstration purposes, there is extra code to create a `JdbcTemplate`, query the database, and print out the names of people the batch job inserts. - - -Build an executable JAR ------------------------ -Add the following to your `pom.xml` file, keeping existing properties and plugins intact: - - {!include:complete/pom.xml#shade-config} - -Create a single executable JAR file containing all necessary dependency classes: - - $ mvn package - - -Run the batch job ------------------ - -Now you can run the job from the JAR as well, and distribute that as an executable artifact: - - $ java -jar target/gs-batch-processing-complete-0.1.0.jar - - -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. - -Summary -------- - -Congratulations! You built a batch job that ingested data from a spreadsheet, processed it, and wrote it to a database. - -[zip]: https://github.com/springframework-meta/gs-batch-processing/archive/master.zip