Indexing Maps

The unordered indexes are used to perform equality queries, also known as the point queries, e.g., name = 'Alice'. These are specifically optimized for equality queries and don’t support other comparison operators like > or <=.

Additionally, the composite unordered indexes allow speeding up the equality queries involving multiple attributes simultaneously, e.g., name = 'Alice' and age = 33. This example query results in a single composite index lookup operation which can be performed very efficiently.

The unordered composite index on the name and age attributes may be configured for a map as follows:

The attributes indexed by the unordered composite indexes can’t be matched partially: the name = 'Alice' query can’t utilize the composite index configured above.

The ordered indexes are specifically designed to perform efficient order comparison queries, also known as the range queries, e.g., age > 33. The equality queries, like age = 33, are still supported by the ordered indexes, but they are handled in a slightly less efficient manner comparing to the unordered indexes.

The composite ordered indexes extend the concept by allowing multiple equality predicates and a single order comparison predicate to be combined into a single index query operation. For instance, the name = 'Alice' and age > 33 and name = 'Bob' and age = 33 and balance > 0.0 queries are good candidates to be covered by an ordered composite index configured as follows:

Unlike the unordered composite indexes, partial attribute prefixes may be matched for the ordered composite indexes. In general, a valid non-empty attribute prefix is formed as a sequence of zero or more equality predicates followed by a zero or exactly one order comparison predicate. Given the index definition above, the following queries may be served by the index: name = 'Alice', name > 'Alice', name = 'Alice' and age > 33, name = 'Alice' and age = 33 and balance = 5.0. The following queries can’t be served the index: age = 33, age > 33 and balance = 0.0, balance > 0.0.

While matching the ordered composite indexes, multiple order comparison predicates acting on the same attribute are treated as a single range predicate acting on that attribute. Given the index definition above, the following queries may be served by the index: name > 'Alice' and name < 'Bob', name = 'Alice' and age > 33 and age < 55, name = 'Alice' and age = 33 and balance > 0.0 and balance < 100.0.

The order of attributes involved in a query plays no role in the selection of the matching composite index: name = 'Alice' and age = 33 and age = 33 and name = 'Alice' queries are equivalent from the point of view of the index matching procedure.

The attributes involved in a query can be matched partially by the composite index matcher: name = 'Alice' and age = 33 and balance > 0.0 can be partially matched by the name, age composite index, the name = 'Alice' and age = 33 predicates are served by the matched index, while the balance > 0.0 predicate is processed by other means.

In the simplest form, bitmap index for an IMap entry attribute can be declaratively configured as follows:

Internally, a unique non-negative long ID is assigned to every indexed IMap entry based on the entry key. That unique ID is required for bitmap indexes to distinguish one indexed IMap entry from another.

The mapping between IMap entries and long IDs is not free and its performance and memory footprint can be improved in certain cases. For instance, if IMap entries already have a unique integer-valued attribute, the attribute values can be used as unique long IDs directly without any additional transformations. That can be configured as follows:

The index definition above instructs Hazelcast to create a bitmap index on the age attribute, extract the unique key values from uniqueId attribute and use the raw (RAW) extracted values directly as long IDs. If the extracted unique key value is not of long type, the widening conversion is performed for the following types: byte, short and int; boxed variants are also supported.

In certain cases, the extracted raw IDs might be randomly distributed. This causes increased memory usage in bitmap indexes since the best case scenario for them is sequential contiguous IDs. That can be countered by applying the renumbering technique:

The index definition above instructs the bitmap index to extract the unique keys from uniqueId attribute, convert every extracted non-negative value to long (LONG) and assign an internal sequential unique long ID based on that extracted and then converted unique value. The widening conversion is applied to the extracted values, if necessary.

This long-to-long mapping is performed more efficiently than the general object-to-long mapping done for the simple index definitions. Basically, the following simple bitmap index definition:

is equivalent to the following full-form definition:

Which indexes age attribute, uses IMap entry keys (__key) interpreted as Java objects (OBJECT) to assign internal unique long IDs.

The full-form definition syntax is defined as follows:

The following are the parameter descriptions:

The regular dotted attribute path syntax is supported for <attr> and <key>:

Collection and array indexing is also possible using the regular syntax:

See Indexing in Collections and Arrays section for more details.

The underlying data structures used by the indexes need to copy the query results to make sure that the results are correct. This copying process is performed either when reading the index from the data structure (on-read) or writing to it (on-write).

On-read copying means that, for each index-read operation, the result of the query is copied before it is sent to the caller. Depending on the query result’s size, this type of index copying may be slower since the result is stored in a map, i.e., all entries need to have the hash calculated before being stored. Unlike the index-read operations, each index-write operation is fast, since there is no copying. So, this option can be preferred in index-write intensive cases.

On-write copying means that each index-write operation completely copies the underlying map to provide the copy-on-write semantics and this may be a slow operation depending on the index size. Unlike index-write operations, each index-read operation is fast since the operation only includes accessing the map that stores the results and returning them to the caller.

Another option is never copying the results of a query to a separate map. This means the results backed by the underlying index-map can change after the query has been executed (such as an entry might have been added or removed from an index, or it might have been remapped). This option can be preferred if you expect "mostly correct" results, i.e., if it is not a problem when some entries returned in the query result set do not match the initial query criteria. This is the fastest option since there is no copying.

You can set one of these options using the system property hazelcast.index.copy.behavior. The following values, which are explained in the above paragraphs, can be set:

The following is an example configuration snippet:

See also the Configuring with System Properties section for reference.

You can also define custom attributes that may be referenced in predicates, queries and indexes. Custom attributes can be defined by implementing a ValueExtractor. See the Custom Attributes section for details.

You can use the keyword this as an attribute name while adding an index or creating a predicate. A basic usage is shown below.

Another basic example using SQL predicate is shown below.

The special attribute this acts on the value of a map entry. Typically, you do not need to specify it while accessing a property of an entry’s value, since its presence is implicitly assumed if the special attribute __key is not specified.