This chapter provides instructions for querying Coherence caches from C++ clients.
This chapter includes the following sections:
Coherence can perform queries and indexes against currently cached data that meets a given set of criteria. Queries and indexes can be simple, employing filters packaged with Coherence, or they can be run against multi-value attributes such as collections and arrays. The result set may be sorted if desired. Queries are evaluated with Read Committed isolation.
It should be noted that queries apply only to currently cached data (and do not use the CacheLoader interface to retrieve additional data that may satisfy the query). Thus, the data set should be loaded entirely into cache before queries are performed. In cases where the data set is too large to fit into available memory, it may be possible to restrict the cache contents along a specific dimension (for example, "date") and manually switch between cache queries and database queries based on the structure of the query. For maintainability, this is usually best implemented inside a cache-aware data access object (DAO).
Indexing requires the ability to extract attributes on each Partitioned cache node; For dedicated CacheServer instances, this implies (usually) that application classes must be installed in the CacheServer classpath.
For Local and Replicated caches, queries are evaluated locally against unindexed data. For Partitioned caches, queries are performed in parallel across the cluster, using indexes if available. Coherence includes a Cost-Based Optimizer (CBO). Access to unindexed attributes requires object deserialization (though indexing on other attributes can reduce the number of objects that must be evaluated).
Querying cache content is very simple, as Example 11-1 illustrates:
Example 11-1 Querying Cache Content
ValueExtractor::Handle hExtractor = ReflectionExtractor::create("getAge");
Filter::View vFilter = GreaterEqualsFilter::create(hExtractor, Integer32::valueOf(18));
for (Iterator::Handle hIter = hCache->entrySet(vFilter)->iterator(); hIter->hasNext(); )
{
Map::Entry::Handle hEntry = cast<Map::Entry::Handle>(hIter->next());
Integer32::View vKey = cast<Integer32::View>(hEntry->getKey());
Person::Handle hPerson = cast<Person::Handle>(hEntry->getValue());
std::cout << "key=" << vKey << " person=" << hPerson;
}
Coherence provides a wide range of filters in the coherence::util::Filter package. A LimitFilter may be used to limit the amount of data sent to the client, and also to provide "paging" for users:
Example 11-2 Using the LimitFilter Method
int32_t nPageSize = 25;
ValueExtractor::Handle hExtractor = ReflectionExtractor::create("getAge");
Filter::View vFilter = GreaterEqualsFilter::create(hExtractor, Integer32::valueOf(18));
// get entries 1-25
LimitFilter::Handle hLimitFilter = LimitFilter::create(vFilter, nPageSize);
Set::View vEntries = hCache->entrySet(hLimitFilter);
// get entries 26-50
hLimitFilter->nextPage();
vEntries = hCache->entrySet(hLimitFilter);
Any queryable attribute may be indexed with the addIndex method of the QueryMap class:
Example 11-3 Indexing a Queryable Attribute
// addIndex(ValueExtractor::View vExtractor, boolean_t fOrdered, Comparator::View vComparator) hCache->addIndex(hExtractor, true, NULL);
The fOrdered argument specifies whether the index structure is sorted. Sorted indexes are useful for range queries, including "select all entries that fall between two dates" and "select all employees whose family name begins with 'S'". For "equality" queries, an unordered index may be used, which may have better efficiency in terms of space and time.
The comparator argument provides a custom java.util.Comparator for ordering the index.
Note:
This method is only intended as a hint to the cache implementation, and as such it may be ignored by the cache if indexes are not supported or if the desired index (or a similar index) exists. It is expected that an application calls this method to suggest an index even if the index exists, just so that the application is certain that index has been suggested. For example, in a distributed environment each server likely suggests the same set of indexes when it starts, and there is no downside to the application blindly requesting those indexes regardless of whether another server has requested the same indexes.
Note that queries can be combined by Coherence if necessary, and also that Coherence includes a cost-based optimizer (CBO) to prioritize the usage of indexes. To take advantage of an index, queries must use extractors that are equal ((Object->equals()) to the one used in the query.
The Partitioned Cache implements the QueryMap interface using the Parallel Query feature and results in high performance queries even for large data sets.
Although queries can be executed through a near cache, the query does not use the front portion of a near cache. If using a near cache with queries, the best approach is to use the following sequence:
Set::View vSetKeys = hCache->keySet(vFilter); Map::View vMapResult = hCache->getAll(vSetKeys);
This section goes into more detail on the design of the query interface, building up from the core components.
The concept of querying is based on the ValueExtractor interface. A value extractor is used to extract an attribute from a given object for querying (and similarly, indexing). Most developers only need the ReflectionExtractor implementation of this interface. The ReflectionExtractor uses reflection to extract an attribute from a value object by referring to a method name, typically a "getter" method like getName().
ReflectionExtractor::Handle hExtractor = ReflectionExtractor::create("getName");
Any void argument method can be used, including Object methods like toString() (useful for prototyping/debugging). Indexes may be either traditional field indexes (indexing fields of objects) or function-based indexes (indexing virtual object attributes). For example, if a class has field accessors getFirstName and getLastName, the class may define a function getFullName which concatenates those names, and this function may be indexed.
To query a cache that contains objects with getName attributes, a Filter must be used. A filter has a single method which determines whether a given object meets a criterion.
Filter::Handle hEqualsFilter = EqualsFilter::create(hExtractor, String::create("Bob Smith"));
To select the entries of a cache that satisfy a particular filter:
Example 11-4 Selecting Entries of a Cache that Satisfy a Particular Filter
for (Iterator::Handle hIter = hCache->entrySet(hEqualsFilter)->iterator(); hIter->hasNext(); )
{
Map::Entry::Handle hEntry = cast<Map::Entry::Handle>(hIter->next());
Integer32::View vKey = cast<Integer32::View>(hEntry->getKey());
Person::Handle hPerson = cast<Person::Handle>(hEntry->getValue());
std::cout << "key=" << vKey << " person=" << hPerson;
}
To select and also sort the entries:
Example 11-5 Selecting and Sorting Entries
// entrySet(Filter::View vFilter, Comparator::View vComparator) Iterator::Handle hIter = hCache->entrySet(hEqualsFilter, NULL)->iterator();
The additional NULL argument specifies that the result set should be sorted using the "natural ordering" of Comparable objects within the cache. The client may explicitly specify the ordering of the result set by providing an implementation of Comparator. Note that sorting places significant restrictions on the optimizations that Coherence can apply, as sorting requires that the entire result set be available before sorting.
Using the keySet form of the queries—combined with getAll()—may provide more control over memory usage:
Example 11-6 Using the keySet Form of a Query
// keySet(Filter::View vFilter)
Set::View vSetKeys = hCache->keySet(vFilter);
Set::Handle hSetPageKeys = HashSet::create();
int32_t PAGE_SIZE = 100;
for (Iterator::Handle hIter = vSetKeys->iterator(); hIter->hasNext();)
{
hSetPageKeys->add(hIter->next());
if (hSetPageKeys->size() == PAGE_SIZE || !hIter->hasNext())
{
// get a block of values
Map::View vMapResult = hCache->getAll(hSetPageKeys);
// process the block
// ...
hSetPageKeys->clear();
}
}
Coherence supports indexing and querying of multi-value attributes including collections and arrays. When an object is indexed, Coherence verifies if it is a multi-value type, and then indexes it as a collection rather than a singleton. The ContainsAllFilter, ContainsAnyFilter, and ContainsFilter are used to query against these collections.
Example 11-7 Indexing and Querying Multi-Value Attributes
Set::Handle hSearchTerms = HashSet::create();
hSearchTerms->add(String::create("java"));
hSearchTerms->add(String::create("clustering"));
hSearchTerms->add(String::create("books"));
// The cache contains instances of a class "Document" which has a method
// "getWords" which returns a Collection<String> containing the set of
// words that appear in the document.
ValueExtractor::Handle hExtractor = ReflectionExtractor::create("getWords");
Filter::View vFilter = ContainsAllFilter::create(hExtractor, hSearchTerms);
Set::View vEntrySet = hCache->entrySet(vFilter);
// iterate through the search results
// ...
The ChainedExtractor implementation allows chained invocation of zero-argument (accessor) methods. In Example 11-8, the extractor first uses reflection to call getName() on each cached Person object, and then use reflection to call length() on the returned String. This extractor could be passed into a query, allowing queries (for example) to select all people with names not exceeding 10 letters.
Example 11-8 Using a ChainedExtractor Implementation
ChainedExtractor::Handle hExtractor =
ChainedExtractor::create(ChainedExtractor::createExtractors("getName.length"));
Method invocations may be chained indefinitely, for example: getName.trim.length.
The QueryRecorder class produces an explain or trace record for a given filter. The class is an implementation of a parallel aggregator that is capable querying all nodes in a cluster and aggregating the results. The class supports two record types: an QueryRecorder::explain record that provides the estimated cost of evaluating a filter as part of a query operation and a QueryRecorder::trace record that provides the actual cost of evaluating a filter as part of a query operation. Both query records take into account whether or not an index can be used by a filter. See Developing Applications with Oracle Coherence for detailed information on understanding the data provided in an explain plan record and trace record.
To create a query record, create a new QueryRecorder instance that specifies a RecordType parameter. Include the instance and the filter to be tested as parameters of the Aggregate method. The following example creates an explain record:
NamedCache::Handle hCache = CacheFactory::getCache("MyCache");
IdentityExtractor::View hExtract = IdentityExtractor::getInstance();
OrFilter::Handle hFilter = OrFilter::create(
GreaterEqualsFilter::create(hExtract, Integer32::create(50)),
LessEqualsFilter::create(hExtract, Integer32::create(20)));
QueryRecord::View vRecord = cast<QueryRecord::View>(hCache->aggregate(
(Filter::View) hFilter, QueryRecorder::create(QueryRecorder::explain)));
cout << vRecord;
To create a trace record, change the RecordType parameter to trace:
QueryRecord::View vRecord = cast<QueryRecord::View>(hCache->aggregate(
(Filter::View) hFilter, QueryRecorder::create(QueryRecorder::trace)));