Secondary Indexes Reference
Note: Riak Search preferred for querying
If you’re interested in non-primary-key-based querying in Riak, i.e. if you’re looking to go beyond straightforward K/V operations, we now recommend Riak Search rather than secondary indexes for a variety of reasons. Riak Search has a far more capacious querying API and can be used with all of Riak’s storage backends.
This document provides implementation and other details for Riak’s secondary indexes (2i) feature.
How It Works
Secondary indexes use document-based partitioning, a system where indexes reside with each document, local to the vnode. This system is also a local index. Secondary indexes are a list of key/value pairs that are similar to HTTP headers. At write time, objects are tagged with index entries consisting of key/value metadata. This metadata can be queried to retrieve the matching keys.
Indexes reside on multiple machines. Since indexes for an object are
stored on the same partition as the object itself, query-time
performance issues might arise. When issuing a query, the system must
read from a “covering” set of partitions and then merge the results.
The system looks at how many replicas of data are stored—the N value
n_val—and determines the minimum number of partitions that it
must examine (1 /
n_val) to retrieve a full set of results, also
taking into account any offline nodes.
An application can modify the indexes for an object by reading an object, adding or removing index entries, and then writing the object. Finally, an object is automatically removed from all indexes when it is deleted. The object’s value and its indexes should be thought of as a single unit. There is no way to alter the indexes of an object independently from the value of an object, and vice versa. Indexing is atomic, and is updated in real time when writing an object. This means that an object will be present in future index queries as soon as the write operation completes.
Riak stores 3 replicas of all objects by default, although this can be changed using bucket types, which manage buckets’ replication properties. The system is capable of generating a full set of results from one third of the system’s partitions as long as it chooses the right set of partitions. The query is sent to each partition, the index data is read, and a list of keys is generated and then sent back to the requesting node.
Note on 2i and strong consistency
Secondary indexes do not currently work with the strong consistency feature introduced in Riak version 2.0. If you store objects in strongly consistent buckets and attach secondary index metadata to those objects, you can still perform strongly consistent operations on those objects but the secondary indexes will be ignored.