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Riak's Java client

README.org

This document describes how to use the Java client to interact with Riak. See the DEVELOPERS document for a technical overview of the project.

Overview

Riak is a dynamo style, distributed key-value store that provides a map reduce query interface. It exposes both a REST and protocol buffers API. This is a Java client for talking to Riak via a single interface, regardless of underlying transport. This library also attempts to simplify some of the realities of dealing with a fault-tolerant, eventually consistent database by providing strategies for:

  • Conflict resolution
  • Retrying requests
  • Value mutation

The client provides some lightweight ORM like capability for storing domain objects in Riak and returning domain objects from map reduce queries.

Using riak-java-client

Including riak-java-client in your project

The current riak-java-client is available from maven central. Add the dependency to your pom.xml

<dependency>
    <groupId>com.basho.riak</groupId>
    <artifactId>riak-client</artifactId>
    <version>0.14.1</version>
    <type>pom</type>
</dependency>

However, that does not include all the new stuff here in master. To get an early feel for the new API you need to build and install from source, first install Apache Maven. With Maven installed, run:

mvn clean install

And set the dependency in your projects pom.xml to

<dependency>
    <groupId>com.basho.riak</groupId>
    <artifactId>riak-client</artifactId>
    <version>0.15-SNAPSHOT</version>
    <type>pom</type>
</dependency>

Quick start

Assuming you’re running Riak on localhost on the default ports getting started is as simple as:

// create a client (see Configuration below in this README for more details)
IRiakClient riakClient = RiakFactory.pbcClient(); //or RiakFactory.httpClient();

// create a new bucket
Bucket myBucket = riakClient.createBucket("myBucket").execute();

// add data to the bucket
myBucket.store("key1", "value1").execute();

//fetch it back
IRiakObject myData = myBucket.fetch("key1").execute();

// you can specify extra parameters to the store operation using the
// fluent builder style API
myData = myBucket.store("key1", "value2").returnBody(true).execute();

// delete
myBucket.delete("key1").rw(3).execute();

Some History

This riak-java-client API is new. Prior to this version there were two separate clients, one for protocol buffers, one for REST, both in the same library and both with quite different APIs.

Deprecated

The REST client (which you can still use directly) has been moved to

com.basho.riak.client.http.RiakClient

Though a deprecated RiakClient still exists at

com.basho.riak.client.RiakClient

for another release or two to ease transition. All the REST client’s HTTP specific classes have been moved to

com.basho.riak.client.http.*

and the originals retained but deprecated. If you want to use the legacy, low-level client directly please use the newly packaged version. The deprecated classes will be deleted in the next or following release to clean up the namespaces.

At that time IRiak* will become Riak* and any I* names will be deprecated then dropped. I’m sorry about the unpleasant naming conventions in the short term.

What’s new?

Builders

To avoid the profusion of constructors and setters there is a builder

com.basho.riak.client.builders.RiakObjectBuilder

to simplify creating and updating IRiakObjects.

In fact most classes are as immutable as possible and are created using fluent builders. The builders are not designed to be used across multiple threads but the immutable value objects they create are.

Layers

Low

There is a low-level interface, RawClient

com.basho.riak.client.raw.RawClient

and two adapters that adapt the legacy protocol buffers and REST clients to the RawClient interface. RawClient provides access to Riak’s APIs. If you don’t want any of the higher level features to deal with domain objects, eventual consistency and fault tolerance (see below) then at least use RawClient over the underlying legacy clients so your code will not need to change if you decide to move from REST to protocol buffers or back. For example:

RiakClient pbcClient = new RiakClient("127.0.0.1");
// OR
// com.basho.riak.client.http.RiakClient httpClient = new
// com.basho.riak.client.http.RiakClient("http://127.0.0.1:8098/riak");
RawClient rawClient = new PBClientAdapter(pbcClient); 
// OR new HTTPClientAdapter(httpClient);

IRiakObject riakObject = RiakObjectBuilder.newBuilder(bucketName, "key1").withValue("value1").build();
rawClient.store(riakObject, new StoreMeta(2, 1, false));
RiakResponse fetched = rawClient.fetch(bucketName, "key1");
IRiakObject result = null;

if(fetched.hasValue()) {
    if(fetched.hasSiblings()) {
    //do what you must to resolve conflicts
    } else {
        result = fetched.getRiakObjects()[0];
    }
}

result.addLink(new RiakLink("otherBucket", "otherKey", "tag"));
result.setValue("newValue");

RiakResponse stored = rawClient.store(result, new StoreMeta(2, 1, true));

IRiakObject updated = null;

if(stored.hasValue()) {
    if(stored.hasSiblings()) {
    //do what you must to resolve conflicts
    } else {
        updated = stored.getRiakObjects()[0];
    }
}

rawClient.delete(bucketName, "key1");

If you want to add a client transport to Riak (say you hate Apache HTTP client but love Netty) implementing RawClient is the way to do it.

High

All the code so far elides somes rather important details:

// handle conflict here

If your bucket allows siblings at some point you may have to deal with conflict. Likewise, if you are running in the real world you may have to deal with temporary failure.

The higher level API (built on top of RawClient) gives you some tools to deal with eventual consistency and temporary failure.

Operations

Talking to Riak is modelled as a set of operations. An operation is a fluent builder for setting operation parameters (like the tunable CAP quorum for a read) and an execute method to carry out the operation. EG

Bucket b = client.createBucket(bucketName)
    .nVal(1)
    .allowSiblings(true)
    .execute();

or

b.store("k", "v").w(2).dw(1).returnBody(false).execute();

All the operations implement RiakOperation<T>, which has a single method:

T execute() throws RiakException;

Retry

Each operation needs a Retrier. You can specify a default retrier implementation when you create an IRiakClient or you can provide one to each operation when you build it. There is a simple retrier provided with this library that retries the given operation n times before throwing an exception.

b.store("k", "v").retrier(DefaultRetrier.attempts(3)).execute();    

The DefaultRiakClient implementation provides a 3 times retrier to all it’s operations. You can override this from the constructor or provide your own per operation (or per bucket, see below). The Retrier interface accepts Callable<T> for its “attempt” method. Internally, operations are built around that interface.

public interface Retrier {
    <T> T attempt(Callable<T> command) throws RiakRetryFailedException;
}

Buckets

To simplify the Riak client all value related operations are performed via the Bucket interface. The Bucket also provides access to the set of bucket properties (nval, allow_mult etc).

NOTE: at present not all bucket properties are exposed by either API. This is something that will be addressed very soon.

One thing to note is that you can store more than just IRiakObjects in buckets. Bucket has convenience methods to store byte[] and String values against a key but also type parameterized generic fetch and store methods. This allows you to store your domain objects in Riak. Please see Conversion below for details.

Although it is expensive and somewhat ill advised, you may list a bucket’s keys with:

for(String k : bucket.keys()) {
     // do your key thing
}

The keys are streamed, and the stream closed by a reaper thread when the iterator is weakly reachable.

There is a further wrapper to bucket (see DomainBucket below) that simplifies calling operations further.

Conflict Resolution

Conflict happens in Dynamo style systems. It is best to have a strategy in mind to deal with it. The strategy you employ is highly dependant on your domain. One example is a shopping cart. Conflicting shopping carts should be merged by a union of their contents, you might reinstate a deleted toaster but that is better than losing money.

See MergeCartResolver in src/test for an example of a Shopping Cart conflict resolver.

Both fetch and store make use of a ConflictResolver to handle siblings.

The default conflict resolver does not “resolve” conflicts, it blows up with an UnresolvedConflictException (which gives you access to the siblings).

Using the basic bucket interface you can provide a conflict resolver to either a fetch or a store operation. All operations are configured by default with a resolver for which siblings are an exception.

The conflict resolver interface is a single method that accepts a Collection of domain objects and returns the one true value, or throws an exception of conflict cannot be resolved. UnresolvedConflictException contains all the siblings. In cases were logic fails to resolve the conflict you can push the decision to a user:

T resolve(final Collection<T> siblings) throws UnresolvedConflictException;

Since conflict resolution requires domain knowledge it makes sense to convert riak data into domain objects.

Conversion

Data in riak is made up of the value, its content-type, links and user meta data. There is then some riak meta data along with that (for example, the VClock, last update time etc.)

The data payload can be any type you like, but normally it is a serialized version of some application specific data. It is a lot easier to reason about siblings and conflict with the domain knowledge of your application, and easier still with the actual domain objects.

Each operation provided by Bucket can accept an implementation of

com.basho.riak.client.convert.Converter

Converter has two methods

IRiakObject fromDomain(T domainObject, VClock vclock)
T toDomain(IRiakObject riakObject)

Implement these and pass to a bucket operation to convert riak data into POJOs and back.

This library currently provides a JSONConverter that uses the Jackson JSON library. Jackson requires your classes to be either simple Java Bean types (getter, setter, no arg constructor) or annotated. Please see

com.megacorp.commerce.ShoppingCart

for an example of Jackson annotated domain class and LegacyCart in the same package for an unannotated class.

You can annotate a field of your class with

@RiakKey

and the client will use the value of that field as the key for fetch and store operations. If you do not or cannot annotate a key field then you must use the

bucket.store("key", myObject);

Implementing your own converter is pretty simple, so if you want to store XML, go ahead. Be aware that the converter should write the content-type when serializing and also check the content-type when deserializing.

There is also a pass through converter for IRiakObject.

You may also use the JSONConverter to store Java Collection types (like Map, List or Map<List> and List<Map<String, List<String>>>) as JSON in Riak. Which is pretty cool.

Mutation

With conflict resolution comes Mutation. When you perform a store you might be creating a new key/value but you may well be updating an existing value and you don’t know in advance. If you model your data to be logically monotonic then you can provide a Mutation<T> that accepts the old value and returns the new value based on some logic.

b.store("k", myObject).withMutation(new Mutation<MyClass>() {
     MyClass apply(MyClass original) {
          myObject.setCounter(orignal.getCounter() +1 );
          return myObject;
     }).execute();

The Mutation<T> interface has a single method:

T apply(T original);

Which accepts the conflict resolved value from a fetch and returns it updated.

The default mutation replaces the old value with the new value. (See ClobberMutation.)

The order of events

When a fetch operation is executed the order of execution is as follows:

  1. RawClient fetch
  2. Siblings iterated and converted
  3. Converted siblings passed to conflict resolver
  4. Resolved value returned

For a store operation

  1. Fetch operation performed as above
  2. The Mutation is applied to the fetched value
  3. The mutated value is converted to RiakObject
  4. The store is performed through the RawClient
  5. if returnBody is true the siblings are iterated, converted and conflict resolved and the value is returned

Domain Buckets

A DomainBucket is a wrapper around a bucket that simplifies the amount of typing and repetition required to work with that bucket. A DomainBucket is an abstraction that allows you to store and fetch specific types in Riak. BEWARE there is no enforcement of any schema on the Riak side, if you store ShoppingCart in the “carts” bucket and try and retrieve it through a DomainBucket<Account> then you will have a ConversionException.

Chances are, that once you project has stablised you will be working with maybe a few types and a few buckets, so you ShoppingCarts will always require that you use you MergedCartResolver and your CartConverter and your CartMutation.

Creating a DomainBucket is easy:

final DomainBucket<ShoppingCart> carts = DomainBucket.builder(b, ShoppingCart.class)
    .withResolver(new MergeCartResolver())
    .returnBody(true)
    .retrier(new DefaultRetrier(4))
    .w(1)
    .dw(1)
    .r(1)
    .rw(1)
    .mutationProducer(new CartMutator())
.build();

Thereafter there is less noise when working with your ShoppingCart data:

final ShoppingCart cart = new ShoppingCart(userId);
cart.addItem("coffee");
cart.addItem("fixie");
cart.addItem("moleskine");
final ShoppingCart storedCart = carts.store(cart);

carts.fetch(userId);
cart.addItem("bowtie");
cart.addItem("nail gun");
carts.delete(cart);

(NOTE: by default a DomainBucket is configured with the DefaultResolver, ClobberMutation and JSONConverter)

Queries

The Riak-java-client currently supports map reduce and link walking.

Map reduce

Performing map reduce is very much as it was for the legacy RiakClient:

Refer to the Riak Map/Reduce documentation for a detailed explanation of how map/reduce works in Riak. Map/Reduce is just another RiakOperation and so a fluent builder:

MapReduceResult result = client.mapReduce("myBucket")
    .addLinkPhase("bucketX", "test", false)
    .addMapPhase(new NamedJSFunction("Riak.mapValuesJson"), false)
    .addReducePhase(new NamedErlangFunction("riak_kv_mapreduce", "reduce_sort"), true)
.execute();

The Map reduce operation lets you build up a number of phases. The MapReduceResult uses Jackson (again) to provide you query results as either Java Collection types, a raw JSON string or (again) as a Java Bean type that you provide to the getResult method:

Collection<GoogleStockDataItem> stockItems =
                result.getResult(GoogleStockDataItem.class);

The inputs to a Map/Reduce are either a bucket, or bucket/key pairs.

Bucket Map Reduce

A BucketMapReduce extends MapReduce. To create a BucketMapReduce operation call

client.mapReduce("myBucket");

BucketMapReduce also allows the addition of Key Filters to limit the results. Adding Key Filters is just like adding phases:

MapReduceResult result = client.mapReduce("myBucket")
.addKeyFilter(new TokenizeFilter("_", 2))
.addKeyFilter(new StringToIntFilter())
.addKeyFilter(new LessThanFilter(50))
.addMapPhase(new NamedJSFunction("Riak.mapValuesJson"))
.addReducePhase(new NamedErlangFunction("riak_kv_mapreduce","reduce_sort"), true)
.execute();

Collection<Integer> items = result.getResult(Integer.class);

Please see the Key Filters documentation for more details about key filters and the

com.basho.riak.client.query.filters.*

package for the available filters.

BucketKeyMapReduce

A BucketKeyMapReduce can be built with many inputs, they’re added just like phases.

MapReduceResult result = client.mapReduce()
    .addInput("goog","2010-01-04")
    .addInput("goog","2010-01-05")
    .addInput("goog","2010-01-06")
    .addInput("goog","2010-01-07")
    .addInput("goog","2010-01-08")
    .addMapPhase(new NamedJSFunction("Riak.mapValuesJson"), true)
.execute();

SearchMapReduce

Riak Search queries can be used as inputs to Map/Reduce. To use a Riak Search query as input for a Map/Reduce operation with the Riak-java-client create a SearchMapReduce operation with the IRiakClient:

MapReduceResult result = client.mapReduce("my_search_bucket", "foo:zero")
    .addMapPhase(new NamedJSFunction("Riak.mapValuesJson"))
    .execute();

And work with the results as before.

To enable a bucket for Riak Search, there is a new method added to Bucket, just call:

client.createBucket("bucket_name") // or updateBucket("bucket_name")
        .enableForSearch().execute()

Note: At present, enabling a bucket only works if your client is an HTTP client. These bucket properties will soon be available via PB. Querying via Map/Reduce works for either transport

IndexMapReduce

An IndexMapReduce can be used if you have the riak_kv_eleveldb_backend enabled. A secondary indexes query can then provide the input for a Map/Reduce job. As before, use the IRiakClient as a factory to create an IndexMapReduce:

IndexQuery iq = new BinValueQuery(BinIndex.named("email"),
    "user_bucket", "user@domain.com");
MapReduceResult result = client.mapReduce(iq)
                            .addReducePhase(NamedErlangFunction.REDUCE_IDENTITY)
                            .execute();

There are query classes to perform a RangeQuery or a ValueQuery.

You can also directly fetch an index using a Bucket:

// fetch int range
List<String> ageRange = b.fetchIndex(IntIndex.named("age")).from(16).to(64).execute();

Link Walking

Links provide a light weight graph database-like feature to Riak. See the Link Walking documentation for full details.

Adding links to an IRiakObject is done via the builder

IRiakObject o = RiakObjectBuilder.newBuilder("myBucket",
"myKey").withValue("value").addLink("bucketX", "keyY", "tagZ").build();

Link Walking is just another RiakOperation. You start at a IRiakObject and add steps to walk and call execute. Adding a step is matter of specifying the bucket, tag and whether to keep the output for the step. A null, empty string or “_” are treated as the wildcard for either of bucket or tag. Specify keep as either a boolean or the Accumulate enum. Not specifying keep will result in the default for that step being used.

An example link walk:

WalkResult result = client.walk(riakObject)
    .addStep(bucketName, fooTag, true)
    .addStep(bucketName, fooTag)
  .execute();

The result is always a Collection of IRiakObjects. In the next version conversion and conflict resolution will also be available to link walking. We also plan to add Link mapping so that links can be used to build graphs of domain objects.

NOTE: Link walking is a REST only operation as far as Riak’s interfaces are concerned. Link Walking in the protocol buffers Java client is a hack that issues two m/r jobs to the protocol buffers interface (the first constructs the inputs to the second by walking the links, the second returns the data). It is included to provide parity between the interfaces but should perform similarly to the REST link walking interface.

Configuration

The riak-java-client takes a layered approach to architecture. There are the 2 legacy clients (http.RiakClient and pbc.RiakClient) which are adapted to the RawClient interface, which itself is wrapped in an IRiakClient implementation when exposing the high-level API. In order to configure the transport at the lowest level, from the high-level there is the RiakFactory and the Configuration interface.

To create a client for the transport of your choice, create a Configuration for that transport and pass it RiakFactory.newClient(Configuration);

 PBClientConfig conf = new PBClientConfig.Builder()
                            .withHost("127.0.0.1")
                             .withPort(8097)
                           .build();

IRiakClient client = RiakFactory.newClient(conf);

There are Configuration implementations for HTTP, Protocal Buffers and a new Configuration for ClusterClient.

A ClusterClient is a set of homogenous RawClients that are configured for many nodes in a Riak cluster and round robined between for requests and retries. This means that you can create your DefaultRetrier to retry as many times as you have nodes in your cluster to exhaustively try each node if the previous one failed to satisfy a request. To create a ClusterClient create a ClusterClientConfig and pass it to RiakFactory.newClient(Configuration).

PBClientConfig node1 = new PBClientConfig.defaults();
PBClientConfig node2 = PBClientConfig.Builder.from(node1).withHost("mysecond-node.com").build();

PBClusterConfig clusterConf = new PBClusterConfig(200);
clusterConf.addClient(node1);
clusterConf.addClient(node2);

RiakFactory.newClient(clusterConf);

At the moment only cluster clients of homogenous transports are supported.

Connection Pools

The Riak HTTP Client uses Apache HTTP Client 4.1. The Apache HTTP Client provides connection pooling and you configure maximum connections per host or cluster (if you are using a ClusterClient)

The riak-java-client provides a connection pool for the protocol buffers client, too. Again you configure per node and over all for the cluster.

Pool Sizing

Both transport’s pools are configured with a connection wait timeout. If you see a lot of exceptions timing out acquiring a connection then the chances are you have sized your pool too small. The API docs have more details on this. See the DEVELOPERS document for instructions on building the API docs.

Next Steps

Have a look at the

com.basho.riak.client.itest

package for examples of all the features described above.

Start storing data in Riak using IRiakObject and anonymous inner classes for Mutation, ConflictResolution and Retrier. As your use case and application firm you can create concrete, testable, reusable implementations to act on your own domain objects.

Contributing

Please start with the DEVELOPERS document.

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