Maven:
<dependency>
<groupId>com.jparams</groupId>
<artifactId>data-store</artifactId>
<version>3.x.x</version>
</dependency>
Gradle:
compile 'com.jparams:data-store:3.x.x'
Data Store is a full-featured indexed Java Collection capable of ultra-fast data lookup. But don't take my word for it, run the benchmark yourself!
Here is one I ran earlier...
Fast, huh!
So how does it work? Well, Data Store, or “Store” for short, builds on top of java.util.Collection, providing a standard interface for adding, removing and iterating elements. This is where other implementation of java.util.Collection stop, but Data Store does a lot more. Data Store provides the ability to add multiple indexes on the elements stored in the collection. The indexing adds a slight overhead when adding elements into the collection, but makes element lookup ridiculously quick.
Whilst indexing is the key functionality we are trying to promote with this library, we have made an effort to ensure that Data Store is a delight to use. Do you need a synchronized Data Store for your multi-threaded environment? How about an unmodifiable view of your Data Store? Maybe you just want to copy an existing Data Store quickly and easily? You can do all this and more!
Creating a Data Store is easy!
Store<Person> store = new MemoryStore<>();There we go, a shiny new Store has been created. Go ahead and use this as you would any other implementation of java.util.Collection. Add, remove, clear.. all the usual methods.
In case you were wondering, MemoryStore is the default implementation of the Store interface. It is a "Memory" Store because it holds all elements added to the Store in memory.
Lets go ahead and use our Store. Here is some of the cool stuff you can do!
Index your Store and enable ultra-fast data lookup. It is as simple as calling the index method. Here goes.....
store.index("firstName", Person::getFirstName);Easy, right?! With our index created, lets query some data and lets query them fast!
List<Person> result1 = store.get("firstName", "James");Let's do something a bit more advanced and work with multiple indexes!
store.index("firstName", Person::getFirstName);
store.index("lastName", Person::getLastName);
// Lets do a more advanced query
Person person = store.getFirst(Query.where("firstName", "james").and("lastName", "smith"));Data Store is backed by hash maps, so this lookup is quick. No looping required.
If you are still not sold on this awesome framework and want more indexing goodness, read on to learn about Reducers and Comparison Policies.
A reducer provides a mechanism for reducing all values that map to the same key.
You can use a limiting reducer to limit the number of values associated with a single index. Say, we only want to index the first 2 people with the first name James, well we can do this using a reducer.
Example:
Index<Person> index = store.index(IndexDefinition.withKeyMapping(Person::getFirstName).withReducer(new MinReducer(2, Retain.OLDEST)));This means that index.get("James") will only ever produce a max of two results. All other people will the first name James will not be indexed.
Say, we want to group by first name then reduce the group down by the date of birth, well we can do this using a Min reducer. This means that we can easily find the youngest person with the given first name.
Example:
Index<Person> index = store.index(IndexDefinition.withKeyMapping(Person::getFirstName).withReducer(new MinReducer(Person::getDateOfBirth, false)));This means that index.get("James") will only ever produce a max of two results. All other people will the first name James will not be indexed.
Say, we want to group by first name then reduce the group down by the date of birth, well we can do this using a Max reducer. This means that we can easily find the oldest person with the given first name.
Example:
Index<Person> index = store.index(IndexDefinition.withKeyMapping(Person::getFirstName).withReducer(new MaxReducer(Person::getDateOfBirth, false)));Lets build on top of the already powerful indexing feature by introducing Comparison Policies. These policies define how indexes are created and how they are matched.
Here are some available out of the box, but feel free to write your own!
Use this policy for creating case insensitive indexes. Example:
// Create a store
Store<Person> store = new MemoryStore<>();
// Add a case insensitive index
Index<Person> index = store.index(IndexDefinition.withKeyMapping(Person::getLastName).withComparisonPolicy(new CaseInsensitiveComparisonPolicy()));
// Query index - these will produce the same result
index.get("James");
index.get("JAMES");
index.get("james");
index.get("JAMes");Comparison policy for comparing two OffsetDateTime values normalized to an UTC time offset.
// Create a store
Store<Person> store = new MemoryStore<>();
// Add a case insensitive index
Index<Person> index = store.addIndex(Person::getLastActive, new OffsetDateTimeComparisonPolicy());
// Query index - these will produce the same result
index.get(OffsetDateTime.of(LocalDateTime.of(2018, 5, 5, 13, 55, 30), ZoneOffset.ofHours(2)));
index.get(OffsetDateTime.of(LocalDateTime.of(2018, 5, 5, 14, 55, 30), ZoneOffset.ofHours(3)));
index.get(OffsetDateTime.of(LocalDateTime.of(2018, 5, 5, 15, 55, 30), ZoneOffset.ofHours(4)));For that extra continence, data store comes with a builder. If you want to do more with a single line of code, we have you covered.
Example:
Store<Person> store = MemoryStore.<Person>newStore()
.withIndex("firstName", Person::getFirstName)
.withIndex("lastName", IndexDefinition.withKeyMapping(Person::getLastName).withComparisonPolicy(new CaseInsensitiveComparisonPolicy()))
.withValues(person1, person32)
.build();This library is compatible with Java 8 and above.
Copyright 2017 JParams
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