Tuesday, October 27, 2015

Approximating tuples in Java

What is a tuple? It's an ordered collection of individually typed elements. Wikipedia has a complicated explanation that comes down to the same thing in the context of ordinary programming. The Python implementation of tuples is a good example.

There are many related concepts, such as:

Arrays and lists
Ordered but all elements are the same type
Ordered dictionaries (maps)
Ordered but all values are of the same type, and they are named
Aggregates (structs, unions)
Individually typed but named and unordered

The closest matches to tuples in current Java are "structs" (more below) and arrays or lists, each with drawbacks. For most use of tuples, arrays and lists are non-starters: elements are all of the same nominal type. There is a lot of thought around how to do this best in Java.

What do I mean by saying Java has "structs" ala "C"? The vast bulk of Java code hides fields away with private, but exposes them with getter methods (and setters when non-final). This is the "Java Bean" anti-pattern. An alternative is to simply expose fields directly:

public final class CartesianPoint {
    public final int x;
    public final int y;

    public CartesianPoint(int x, int y) {
        this.x = x;
        this.y = y;
    }
}

This is almost a tuple. However:

  • CartesianPoint extends java.lang.Object but should not be an object in the OOP sense
  • Elements are accessed by name, e.g., point.x, rather than position
  • Elements are unordered—you cannot write a general function to process the first and second elements of the tuple without knowing 1) the struct type and 2) the names of the fields

But for many use cases this can be close enough, for example as a return type to simulate multiple value return. Hopefully Java 10 brings value types which resolves the java.lang.Object issue. This may even bring true tuples!

This example can be improved with Lombok:

@EqualsAndHashCode
@RequiredArgsConstructor(staticName = "valueOf")
@ToString(includeFieldNames = false)
public final class CartesianPoint {
    public final int x;
    public final int y;
}

Calling code would look like:

public CartesianPoint locate() {
    int x = computeX();
    int y = computeY();

    return CartesianPoint.valueOf(x, y);
}

Notice the visual similarity of the local variables x and y to the corresponding fields in CartesianPoint. Users of CartesianPoint would see:

public static void main(final String... args) {
    Boat boat = Boat.rowBoat();
    CartesianPoint point = boat.locate();

    out.printf("%s -> x is %d, y is %d%n", point, point.x, point.y);
}

$ ./float-boat 1 2
CartesianPoint(1, 2) -> x is 1, y is 2

If you want to go hog wild, the ordered and unnamed qualities of tuples can be simulated though not without significant noise:

Function<CartesianPoint, Integer> first = p -> p.x;
Function<CartesianPoint, Integer> second = p -> p.y;

out.printf("first is %d, second is %d%n",
        first.apply(point),
        second.apply(point));

Update

Streaming functionally:

Function<CartesianPoint, Integer> first = p -> p.x;
Function<CartesianPoint, Integer> second = p -> p.y;
Stream.of(first, second).
    map(f -> f.apply(point)).
    forEach(out::println);

Monday, October 26, 2015

What's wrong with Java 8 series by Pierre-Yves Saumont

Pierre-Yves Saumont wrote a series of articles for DZone. I feel remiss for having missed them. For example, What's Wrong in Java 8, Part IV: Monads explores java.util.Optional. Do not be misled by the post titles—yes, he criticizes Java 8 for what it could have been—, but he covers functional thinking in Java with depth, skill and panache.

The full list of "What's Wrong with Java 8" articles:

  1. Currying vs Closures
  2. Functions & Primitives
  3. Streams and Parallel Streams
  4. Monads
  5. Tuples
  6. Strictness
  7. Streams again

And all his DZone articles.

Wednesday, October 21, 2015

Tracking Java 8 stream count

I had a coding problem to fail when a Java 8 stream was empty. One way is illustrated below in example1. Another approach was interesting, shown in example2

public final class Streamy {
    private static <T, E extends RuntimeException> void example1(
            final Stream<T> items,
            final Consumer<? super T> process,
            final Supplier<E> thrown)
            throws E {
        if (0 == items.
                peek(process).
                count())
            throw thrown.get();
    }

    private static <T, E extends RuntimeException> void example2(
            final Stream<T> items,
            final Consumer<? super T> process,
            final Supplier<E> thrown)
            throws E {
        final AtomicBoolean foundSome = new AtomicBoolean();
        try (final Stream<T> stream = items) {
            stream.
                    onClose(() -> {
                        if (!foundSome.get())
                            throw thrown.get();
                    }).
                    peek(__ -> foundSome.set(true)).
                    forEach(process);
        }
    }

    public static void main(final String... args) {
        example1(Stream.of(), out::println, RuntimeException::new);
        example2(Stream.of(), out::println, RuntimeException::new);
    }
}

Comparing them I find:

  • Using count() is shorter and more clear
  • Using onClose() is more expressive

I found it odd to use peek() in example1 to execute the real purpose of the code, and was happy to discover onClose() though disappointed to need try-with-resources for it to run.

It was unfortunate that the more expressive approach (peek() for side effect, forEach() for processing, onClose for post-processing check) was also harder to understand.

Sunday, October 18, 2015

Downloading sources and javadocs automatically

Thanks to Ted Wise, I taught my "modern java" build to automatically download sources and javadocs. Using maven:

<plugin>
    <artifactId>maven-dependency-plugin</artifactId>
    <version>${maven-dependency-plugin.version}</version>
    <executions>
        <execution>
            <id>download-sources</id>
            <phase>generate-sources</phase>
            <goals>
                <goal>sources</goal>
            </goals>
        </execution>
        <execution>
            <id>download-javadocs</id>
            <phase>generate-sources</phase>
            <configuration>
                <classifier>javadoc</classifier>
            </configuration>
            <goals>
                <goal>resolve</goal>
            </goals>
        </execution>
    </executions>
</plugin>

Saturday, October 17, 2015

Struggling with Travis CI and Maven 3.3

I struggled with fixing Travis CI for my "labs" code. The main problem is lack of support for Maven 3.3; my POM enforcer requires it. Eventually I got something working with help from the Internet, though I'm not happy with it. It manually downloads and uses maven 3.3:

sudo: false
language: java
jdk:
  - oraclejdk8
# TODO: Gross until Travis support setting maven version or upgrades to 3.3
before_install:
  - wget http://apache.claz.org/maven/maven-3/3.3.3/binaries/apache-maven-3.3.3-bin.tar.gz
  - tar zxvf apache-maven-3.3.3-bin.tar.gz
  - chmod +x apache-maven-3.3.3/bin/mvn
  - export M2_HOME=$PWD/apache-maven-3.3.3
  - export PATH=$PWD/apache-maven-3.3.3/bin:${PATH}
  - hash -r
before_script:
  - export M2_HOME=$PWD/apache-maven-3.3.3
  - export PATH=$PWD/apache-maven-3.3.3/bin:${PATH}
  - hash -r
script: mvn verify -Dgpg.skip=true

Bonus

On another project using Travis CI I ran afoul of the 10,000 line limit for displaying build output in the web UI. Workaround, add this to the build_install section:

  - echo 'MAVEN_OPTS="-Dorg.slf4j.simpleLogger.defaultLogLevel=warn"' >~/.mavenrc

If you're using maven 3.3 or better, Karl Heinz Marbaise has a better approach with .mvn/jvm.config.

Thursday, October 15, 2015

Spring advice

Today I had an exchange with an erstwhile colleague, one of those talented few equally comfortable in C++ and Java, great with demanding clients and fellow developers. He asked me for thoughts on Spring dependency injection. Branching out a bit, I replied:

Matter of taste/opinion.

Some things I prefer:

  • Avoid setter injection if at all possible. I want my beans to be finished after DI, not changeable at runtime on accident (very nasty bug to track down) Constructor injection most preferred, followed by field
  • Use standard annotations rather than Spring ones (@Inject), though @Value is needed for injected configuration if you're not using a dedicated configuration object
  • Spring Java configuration beats XML almost all the time
  • If the program doesn't need Spring DI, I prefer using Guice or Dagger. They're simpler, everything is at compile time, and error messages are better. The Spring non-DI libraries play fine with others (e.g., spring-jdbc)
  • Avoid mixing business objects with wiring unless it makes sense. For example, JdbcTemplate should be new'ed as needed, injecting only the DataSource. Injecting the template is an anti-pattern
  • Do use Spring Boot or Dropwizard, et al, if it makes sense. Big time savers, lots of good integration prepackaged
  • For webby programs (apps, services) remember to test unit, controller and integration separately. Spring boot intro page has excellent code examples

Things get more interesting with multiple configurations and with cloud. For example:

  • Do you make separate builds for each env, or one build with multiple configurations? Latter is traditional in EE world, former much better for cloud (devops, immutable, unikernel, etc)
  • Do you pull in configuration externally, e.g., Spring Cloud Config, Netflix Archaius or Apache Zookeeper. I like this approach, but more complex and overkill for simple programs. Nearly mandatory for microservices, and strong choice when in cloud

Did I answer fairly?

Tuesday, October 13, 2015

Blog code 6

(Updated) I've published my blog code version 6 to Maven Central with javadocs. The previous version was 0.5; having a leading "0." was silly (there won't be a 1.0).

Interesting changes:

  • Added the YAML modules. This is an annotation processor which takes YAML descriptions of Java data structures, and generates immutable classes for them.
  • Added the Matching class for a pattern-matching DSL in Java. I'll improve on over time.

Wednesday, October 07, 2015

Automating dependency versions in Maven

Reading the most excellent Modern Java series of posts, I realized I could automate a command line step I always did manually—updating dependency versions:

$ mvn versions:update-properties

I can automate that! The simplest possible POM demonstrating:

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0
         http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>example-group</groupId>
    <artifactId>example-artifact</artifactId>
    <version>0-SNAPSHOT</version>

    <properties>
        <example-dependency.version>1</example-dependency.version>
        <generateBackupPoms>false</generateBackupPoms>
        <versions-maven-plugin.version>2.2</versions-maven-plugin.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>example-group</groupId>
            <artifactId>example-dependency</artifactId>
            <version>${example-dependency.version}</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.codehaus.mojo</groupId>
                <artifactId>versions-maven-plugin</artifactId>
                <version>${versions-maven-plugin.version}</version>
                <executions>
                    <execution>
                        <id>update-dependencies</id>
                        <phase>validate</phase>
                        <goals>
                            <goal>update-properties</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

My hypothetical maven build says:

$ mvn clean
[INFO] Scanning for projects...
[INFO] ------------------------------------------------------------------------
[INFO] Building example-artifact 0-SNAPSHOT
[INFO] ------------------------------------------------------------------------
[INFO]
[INFO] --- maven-clean-plugin:2.5:clean (default-clean) @ example-artifact ---
[INFO]
[INFO] --- versions-maven-plugin:2.2:update-properties (update-dependencies) @ example-artifact ---
[INFO] Property ${example-dependency.version}: Leaving unchanged as 1.2.3
[INFO] Property ${versions-maven-plugin.version}: Leaving unchanged as 2.2

The key is using <phase>validate</phase> in the plugin execution. The first lifecycle phase for maven is "validate". Setting the property "generateBackupPoms" to "false" prevents pom.xml.versionsBackup files from littering the project. You are using source control, aren't you?

Update

This approach is best during development, especially for greenfield projects. I would not recommend it for stable or legacy projects where dependency versions need to be kept constant.

Thursday, September 10, 2015

JUnit @Rule for a SQL transaction

I needed to run some Java test code in a SQL transaction. It modifies the database, changes that should be 1) invisible to other tests, and 2) thrown away after tests finish.

I am using JUnit (of course) so I wrote a @Rule to provide a transaction to my test methods (note I'm using Lombok for convenience):

@RequiredArgsConstructor
public final class SQLTransactionRule
        extends ExternalResource {
    private final DataSource original;
    private final String user;
    private final String password;
    private final Consumer testDataSource;

    private Connection conn;

    public SQLTransactionRule(final DataSource original,
            final Consumer testDataSource) {
        this(original, null, null, testDataSource);
    }

    @Override
    protected void before()
            throws Throwable {
        super.before();
        beginTransaction();
        testDataSource.accept(testDataSource(conn));
    }

    @Override
    protected void after() {
        testDataSource.accept(null);
        rollbackTransaction();
        super.after();
    }

    private void beginTransaction() {
        try {
            final Connection conn = original.getConnection(user, password);
            conn.setAutoCommit(false);
            this.conn = conn;
        } catch (final SQLException e) {
            throw new RuntimeException(
                    format("Cannot create transaction from %s: %s", original,
                            getRootCause(e)), e);
        }
    }

    private void rollbackTransaction() {
        try {
            conn.rollback();
        } catch (final SQLException e) {
            throw new RuntimeException(
                    format("Cannot rollback transaction to %s: %s", original,
                            getRootCause(e)), e);
        }
    }

    private DataSource testDataSource(final Connection conn) {
        return (DataSource) newProxyInstance(getClass().getClassLoader(),
                new Class[]{DataSource.class}, (proxy, method, args) -> {
                    System.out.println("SQLTransactionRule.testDataSource");
                    if (Object.class.equals(method.getDeclaringClass()))
                        return method.invoke(proxy, args);
                    else if ("getConnection".equals(method.getName()))
                        return conn;
                    else
                        return method.invoke(original, args);
                });
    }
}

The motivation for the Consumer of "testDataSource" and for the proxied data source was avoidance of dependencies. Original code has this convenience method, but I decided that was a concern of the test code not the @Rule:

public JdbcTemplate newJdbcTemplate() {
    return new JdbcTemplate(testDataSource);
}

Of course there are tests for the @Rule as well! And this post on Mockito was handy.

@RunWith(MockitoJUnitRunner.class)
public final class SQLTransactionRuleTest {
    @Mock
    private DataSource original;
    @Mock
    private Connection conn;

    @Rule
    public final ExpectedException thrown = ExpectedException.none();

    private SQLTransactionRule rule;
    private DataSource testDataSource;

    @Before
    public void setUp()
            throws SQLException {
        when(original.getConnection(anyString(), anyString())).
                thenReturn(conn);
        rule = new SQLTransactionRule(original,
                testDataSource -> this.testDataSource = testDataSource);
    }

    @Test
    public void shouldExecuteStatement()
            throws Throwable {
        final boolean[] called = {false};
        executeStatement(() -> called[0] = true);
        assertThat(called[0], is(true));
    }

    @Test
    public void shouldPublishTestDataSource()
            throws Throwable {
        executeStatement(
                () -> assertThat(testDataSource, is(notNullValue())));
    }

    @Test
    public void shouldReuseOriginalConnection()
            throws Throwable {
        executeStatement(() -> assertThat(testDataSource.getConnection(),
                is(sameInstance(conn))));
    }

    @Test
    public void shouldTransact()
            throws Throwable {
        executeStatement(() -> verify(conn).setAutoCommit(eq(false)));
        verify(conn).rollback();
    }

    @Test
    public void shouldDescribe()
            throws Throwable {
        thrown.expect(AssertionError.class);
        thrown.expectMessage(containsString("alpha"));
        thrown.expectMessage(containsString("beta"));

        executeStatement(() -> assertThat("alpha", is(equalTo("beta"))));
    }

    @FunctionalInterface
    private interface RunMe {
        void execute()
                throws Throwable;
    }

    private void executeStatement(final RunMe statement)
            throws Throwable {
        rule.apply(new Statement() {
            @Override
            public void evaluate()
                    throws Throwable {
                statement.execute();
            }
        }, EMPTY).evaluate();
    }
}

Saturday, June 27, 2015

REST API best practices

Vinay Sahni of Enchant writes Best Practices for Designing a Pragmatic RESTful API, a complete, current best practices article on REST APIs, chock full of explanation, examples and real APIs from top web sites. Enchant itself is a good example how to document a REST API. Vinay has been writing a long series of articles on REST APIs, plenty of chewy links for further reading. Main points:

  • Key requirements for the API
  • Use RESTful URLs and actions
  • SSL everywhere - all the time
  • Documentation
  • Versioning
  • Result filtering, sorting & searching
  • Limiting which fields are returned by the API
  • Updates & creation should return a resource representation
  • Should you HATEOAS?
  • JSON only responses
  • snake_case vs camelCase for field names
  • Pretty print by default & ensure gzip is supported
  • Don't use an envelope by default, but make it possible when needed
  • JSON encoded POST, PUT & PATCH bodies
  • Pagination
  • Auto loading related resource representations
  • Overriding the HTTP method
  • Rate limiting
  • Authentication
  • Caching
  • Errors
  • HTTP status codes
  • In Summary

Pattern matching for Java

Java does not (yet) have pattern matching although writing a legible DSL for it is not too hard. I'm certainly not the first to take a hand at it.

An example DSL in action. Lambdas and method references sure help a lot:

public static void main(final String... args) {
    asList(0, 1, 2, 3, 13, 14, null, -1).stream().
            peek(n -> out.print(format("%d -> ", n))).
            map(matching(Integer.class, Object.class).
                    when(Objects::isNull).then(n -> "!").
                    when(is(0)).then(nil()).
                    when(is(1)).then("one").
                    when(is(13)).then(() -> "unlucky").
                    when(is(14)).then(printIt()).
                    when(even()).then(scaleBy(3)).
                    when(gt(2)).then(dec()).
                    none().then("no match")).
            map(MatchingTest::toString).
            forEach(out::println);
    out.flush(); // Avoid mixing sout and serr

    matching(Integer.class, Void.class).
            none().thenThrow(RuntimeException::new).
            apply(0);
}

Implementation:

/**
 * {@code Matching} represents <a href="https://en.wikipedia.org/wiki/Pattern_matching">Pattern
 * Matching</a> in Java as a function production an optional.  Example: <pre>
 * asList(0, 1, 2, 3, 13, 14, null, -1).stream().
 *         peek(n -> out.print(format("%d -> ", n))).
 *         map(matching(Integer.class, Object.class).
 *             when(Objects::isNull).then(n -&gt; "!").
 *             when(is(0)).then(nil()).
 *             when(is(1)).then("one").
 *             when(is(13)).then(() -&gt; "unlucky").
 *             when(is(14)).then(printIt()).
 *             when(even()).then(scaleBy(3)).
 *             when(gt(2)).then(dec()).
 *             none().then("no match")).
 *         map(MatchingTest::toString).
 *         forEach(out::println);</pre>
 * <p>
 * <i>NB</i> &mdash; There is no way to distinguish from an empty optional if
 * there was no match, or if a match mapped the input to {@code null}, without
 * use of a {@link When#then(Object) sentinel value} or {@link
 * When#thenThrow(Supplier) thrown exception}.
 * <p>
 * <strong>NB</strong> &mdash; There is no formal destructuring, but this can
 * be simulated in the {@code Predicate} to {@link #when(Predicate) when}.
 *
 * @param <T> the input type to match against
 * @param <U> the output type of a matched pattern
 *
 * @author <a href="mailto:binkley@alumni.rice.edu">B. K. Oxley (binkley)</a>
 */
@NoArgsConstructor(access = PRIVATE)
public final class Matching<T, U>
        implements Function<T, Optional<U>> {
    private final Collection<Case> cases = new ArrayList<>();

    /**
     * Begins pattern matching with a new pattern matcher.
     *
     * @param inType the input type token, never {@code null}
     * @param outType the output type token, never {@code null}
     * @param <T> the input type to match against
     * @param <U> the output type of a matched pattern
     *
     * @return the pattern matcher, never {@code null}
     *
     * @todo Avoid the type tokens
     */
    public static <T, U> Matching<T, U> matching(final Class<T> inType,
            final Class<U> outType) {
        return new Matching<>();
    }

    /**
     * Begins a when/then pair.
     *
     * @param when the pattern matching test, never {@code null}
     *
     * @return the pattern continuance, never {@code null}
     */
    public When when(final Predicate<? super T> when) {
        return new When(when);
    }

    /**
     * Begins a default when/then pair, always placed <strong>last</strong> in
     * the list of cases (evaluates no cases after this one).
     *
     * @return then pattern continuance, never {@code null}
     */
    public When none() {
        return when(o -> true);
    }

    /**
     * Evaluates the pattern matching.
     *
     * @param in the input to match against, possibly {@code null}
     *
     * @return the match result (empty if no match), never {@code null}
     */
    @Override
    public Optional<U> apply(final T in) {
        return cases.stream().
                filter(c -> c.p.test(in)).
                findFirst().
                map(c -> c.q.apply(in));
    }

    @RequiredArgsConstructor(access = PRIVATE)
    public final class When {
        /**
         * Number of frames to discard when creating an exception for a match.
         * Very sensitive to implementation.  This aids in understanding stack
         * traces from matching, discarding internal machinery and leaving the
         * actual throwing call at the top of the stack.
         */
        private static final int N = 7;
        private final Predicate<? super T> when;

        /**
         * Ends a when/then pair, evaluating <var>then</var> against the input
         * if matched.
         *
         * @param then the pattern matching function, never {@code null}
         *
         * @return the pattern matcher, never {@code null}
         */
        public Matching<T, U> then(
                final Function<? super T, ? extends U> then) {
            cases.add(new Case(when, then));
            return Matching.this;
        }

        /**
         * Ends a when/then pair, returning <var>then</var> if matched.
         *
         * @param then the pattern matching value, possibly {@code null}
         *
         * @return the pattern matcher, never {@code null}
         */
        public Matching<T, U> then(final U then) {
            cases.add(new Case(when, x -> then));
            return Matching.this;
        }

        /**
         * Ends a when/then pair, evaluating <var>then</var> independent of
         * supplier if matched.
         *
         * @param then the pattern matching supplier, never {@code null}
         *
         * @return the pattern matcher, never {@code null}
         */
        public Matching<T, U> then(final Supplier<? extends U> then) {
            cases.add(new Case(when, x -> then.get()));
            return Matching.this;
        }

        /**
         * Ends a when/then pair, evaluating <var>then</var> to {@code null}
         * if matched.
         *
         * @param then the input consumer, never {@code null}
         *
         * @return the pattern matcher, never {@code null}
         */
        public Matching<T, U> then(final Consumer<? super T> then) {
            cases.add(new Case(when, o -> {
                then.accept(o);
                return null;
            }));
            return Matching.this;
        }

        /**
         * Ends a when/then pair, evaluating <var>then</var> independent of
         * supplier and throwing the new exception if matched.
         *
         * @param then the pattern matching exception supplier, never {@code
         * null}
         *
         * @return the pattern matcher, never {@code null}
         */
        public Matching<T, U> thenThrow(
                final Supplier<RuntimeException> then) {
            cases.add(new Case(when, x -> {
                final RuntimeException e = then.get();
                final List<StackTraceElement> stack = asList(
                        e.getStackTrace());
                e.setStackTrace(stack.subList(N, stack.size()).
                        toArray(new StackTraceElement[stack.size() - N]));
                throw e;
            }));
            return Matching.this;
        }
    }

    @RequiredArgsConstructor(access = PRIVATE)
    private final class Case {
        private final Predicate<? super T> p;
        private final Function<? super T, ? extends U> q;
    }
}

Thursday, May 28, 2015

RESTful errors, Simple Boot

Handling Errors

Reading Travis McChesney's RESTful API Design Part III: Error Handling, there are more ways to represent errors in REST APIs than the returned body. A toy API I am writing as a playground for these idea is named Simple Boot, a jest on "Spring Boot". There I have an "X-Correlation-ID" header for tracking calls through services.

  • Should "X-Correlation-ID" be required?
  • Should it be supplied automatically?
  • When required and missing, what should the caller receive?

Answering the third the caller sees:

HTTP/1.1 400 Bad Request
Server: Apache-Coyote/1.1
Warning: 250 localhost:8080 "Missing X-Correlation-ID header"
Content-Type: application/json;charset=UTF-8
Transfer-Encoding: chunked
Date: Thu, 28 May 2015 12:46:40 GMT
Connection: close

{
  "timestamp": 1432817125588,
  "status": 400,
  "error": "Bad Request",
  "message": "Missing X-Correlation-ID header",
  "path": "/hello/Bob"
}

Here rather than choosing among options, I take them all:

  1. Return a 400 for a bad request
  2. Describe the error in the response body
  3. Add a header describing the error

As McChesney points out, there is not general agreement on reporting errors. For example, Facebook returns 200 for errors, requiring parsing of the response body.

Using the "Warning" header for this purpose is uncommon but supported in the specification albeit obliquely. However not everyone agrees. I use warning code 250, one I made up. The 1xx codes are transient errors; the 2xx codes permanent. In another example I use a 1xx code for an upstream service currently unavailable, and return cached data, which is closer to the described uses of "Warning".

Other header options:

  • Using a custom code outside 1xx or 2xx with "Warning". This makes sense for in-house services, may cause issues with caching devices but unclear
  • Use a custom HTTP header, a common solution, again may have issues with intermediate devices

Some Spring Bonus

Simple Boot has been fun and instructive. One Spring Boot feature I stumbled on is automated binding of configuration properties. For services requiring "X-Correlation-ID" I configure with @ConfigurationProperties(prefix = "headers.correlation-id.server"). To automate clients I use @ConfigurationProperties(prefix = "headers.correlation-id.client").

As an example of solving one issue with headers, I write Feign pass-through support.

Of course there are tests.