Chronicle-Map/docs/CM_Tutorial.adoc

=  Chronicle Map Tutorial
Neil Clifford
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This document describes the Chronicle Map tutorial supplied with the project.


== Create a `ChronicleMap` Instance

Creating an instance of `ChronicleMap` is a little more complex than just calling a constructor.
To create an instance you have to use the `ChronicleMapBuilder`.

=== In-memory Chronicle Map
The following code snippet creates an in-memory Chronicle Map store, supposed to store about 50 000 _city name -> postal code_ mappings.

It is accessible within a single JVM process; the process in which it was created. The data is accessible while the process is alive. When the process is terminated, the data is cleared.


``` java
import net.openhft.chronicle.map.*
.....

interface PostalCodeRange {
    int minCode();
    void minCode(int minCode);

    int maxCode();
    void maxCode(int maxCode);
}

ChronicleMapBuilder<CharSequence, PostalCodeRange> cityPostalCodesMapBuilder =
    ChronicleMapBuilder.of(CharSequence.class, PostalCodeRange.class)
        .name("city-postal-codes-map")
        .averageKey("Amsterdam")
        .entries(50_000);
ChronicleMap<CharSequence, PostalCodeRange> cityPostalCodes =
    cityPostalCodesMapBuilder.create();

// Or shorter form, without builder variable extraction:

ChronicleMap<Integer, PostalCodeRange> cityPostalCodes = ChronicleMap
    .of(CharSequence.class, PostalCodeRange.class)
    .name("city-postal-codes-map")
    .averageKey("Amsterdam")
    .entries(50_000)
    .create();
```

=== Persisted Chronicle Map

You can amend this code to create a persisted Chronicle Map by replacing `.create()` calls with `.createPersistedTo(cityPostalCodesFile)`, if you want the Chronicle
Map to, either:

 - outlive the process it was created within; for example, to support hot application redeployment.
 - be accessible from multiple concurrent processes on the same server.
 - Persist the data to disk.

The `cityPostalCodesFile` has to represent the same location on your server among all Java
processes that wish to access this Chronicle Map instance; For example, `System.getProperty("java.io.tmpdir") + "/cityPostalCodes.dat"`.

The name and location of the file is entirely up to you.

Note: When you create a `ChronicleMap` instance with `.createPersistedTo(file)`, and the given
file already exists in the system, you open a view to the existing Chronicle Map data store from
this JVM process, rather than creating a new Chronicle Map data store. That is, the data store could already contain some entries. No special action with the data is performed during such operation. If you want to clean up corrupted entries, and ensure that the data store is in correct state, see the <<Recovery>> section.


NOTE: ChronicleMap instance vs Chronicle Map data store +
  +
  In this tutorial, `ChronicleMap` instance (or simply `ChronicleMap`) term is used to refer to on-heap object, providing access to a Chronicle Map data store (or Chronicle Map key-value store, or Chronicle Map store, or simply Chronicle Map, with space between two words in contrast to `ChronicleMap`), which could be purely in-memory, or persisted to disk. Currently Java implementation doesn't allow to create multiple accessor ChronicleMap` objects to a single *in-memory Chronicle Map store*, i. e. there is always a one-to-one correspondence, that may lead to confusion. *Persisted Chronicle Map store*, however, allows to create multiple accessor `ChronicleMap` instances either within a single JVM process (though [it is not recommended to do that](#single-chroniclemap-instance-per-jvm)), or from concurrent JVM processes, that is perfectly OK.

When no processes access the file, it could be freely moved to another location in the system, and
even to another server, even running different operating system, opened from another location and
you will observe the same data.

If you don't need the Chronicle Map instance to survive the server restart, i. e. you don't need
persistence to disk, only multi-process access, choose the file to be mounted on http://en.wikipedia.org/wiki/Tmpfs[tmpfs]; for example, on `Linux` it is as easy as placing you file in `/dev/shm` directory.


==== Configure `.entries(entries)`

Try to configure the `entries` so that the created Chronicle Map is going to serve about 99% requests being less or equal than this number of entries in size.

You should not put additional margin over the actual target number of entries. This bad practice was popularized by `new HashMap(capacity)` and `new HashSet(capacity)` constructors, which accept capacity, that should be multiplied by load factor to obtain the actual maximum expected number of entries in the container. `ChronicleMap` and `ChronicleSet` don't have a notion of load factor.

See `ChronicleMapBuilder#entries()` in http://www.javadoc.io/doc/net.openhft/chronicle-map/[Javadocs] for more information.


Once `ChronicleMap` instance is created, its configurations are sealed and cannot be changed
though the `ChronicleMapBuilder` instance.


==== Single `ChronicleMap` instance per JVM
If you want to access a Chronicle Map data store
concurrently within a Java process, you should not create a separate `ChronicleMap` instance per thread. Within the JVM environment, `ChronicleMap` instance is a `ConcurrentMap`, and could be accessed concurrently the same way as, for example, `ConcurrentHashMap`.

=== Recovery

If a process, accessing a persisted Chronicle Map, terminated abnormally: crashed, `SIGKILL`ed, or
terminated because the host operating system crashed, or the machine lost power, the Chronicle Map
might remain in an inaccessible or corrupted state. When the Chronicle Map is opened next time from
another process, it should be done via `.recoverPersistedTo()` method in `ChronicleMapBuilder`.
Unlike `createPersistedTo()`, this method scans all memory of Chronicle Map store for
inconsistencies, if some found, it cleans them up.

`.recoverPersistedTo()` needs to access the Chronicle Map exclusively. If a concurrent process is
accessing the Chronicle Map while another process is attempting to perform recovery, result of
operations on the accessing process side, and results of recovery are unspecified. The data could be
corrupted further. You must ensure no other process is accessing the Chronicle Map store when
calling for `.recoverPersistedTo()` on this store.

Example:

```java
ChronicleMap<Integer, PostalCodeRange> cityPostalCodes = ChronicleMap
    .of(CharSequence.class, PostalCodeRange.class)
    .name("city-postal-codes-map")
    .averageKey("Amsterdam")
    .entries(50_000)
    .recoverPersistedTo(cityPostalCodesFile, false);
```

The second parameter in `recoverPersistedTo()` method is called
`sameBuilderConfigAndLibraryVersion`, it could be `true` only if `ChronicleMapBuilder` is configured
in exactly the same way, as when the Chronicle Map (persisted to the given file) was created, and
using the same version of the Chronicle Map library, or `false`, if initial configurations are not
known, or current version of Chronicle Map library could be different from the version, used to
create this Chronicle Map initially.

If `sameBuilderConfigAndLibraryVersion` is `true`, `recoverPersistedTo()` "knows" all the right
configurations and what should be written to the header. It checks if the recovered Chronicle Map's
header memory (containing serialized configurations) is corrupted or not. If the header is
corrupted, it is overridden, and the recovery process continues.

If `sameBuilderConfigAndLibraryVersion` is `false`, `recoverPersistedTo()` relies on the
configurations written to the Chronicle Map's header, assuming it is not corrupted. If it is
corrupted, `ChronicleHashRecoveryFailedException` is thrown.

However, the subject header memory is never updated on ordinary operations with Chronicle Map, so it
couldn't be corrupted if an accessing process crashed, or the operating system crashed, or even the
machine lost power. Only hardware memory or disk corruption or a bug in the file system could lead
to Chronicle Map header memory corruption.

`.recoverPersistedTo()` is harmless if the previous process accessing the Chronicle Map terminated
normally, however this is a computationally expensive procedure that should generally be avoided.

Chronicle Map creation and recovery could be conveniently merged using a single call:
`.createOrRecoverPersistedTo(persistenceFile, sameLibraryVersion)` in `ChronicleMapBuilder`, which
acts like `createPersistedTo(persistenceFile)`, if the persistence file doesn't yet exist, and like
`recoverPersistedTo(persistenceFile, sameLibraryVersion)`, if the file already exists, e. g.:

```java
ChronicleMap<Integer, PostalCodeRange> cityPostalCodes = ChronicleMap
    .of(CharSequence.class, PostalCodeRange.class)
    .averageKey("Amsterdam")
    .entries(50_000)
    .createOrRecoverPersistedTo(cityPostalCodesFile, false);
```

If the Chronicle Map is configured to store entry checksums along with entries, recovery procedure
checks for each entry that the checksums is correct, otherwise it assumes the entry is corrupted and
deletes it from the Chronicle Map. If checksums are to stored, recovery procedure cannot guarantee
correctness of entry data. See [Entry checksums](#entry-checksums) section for more information.

=== Key and Value Types

Either key or value type of `ChronicleMap<K, V>` could be:

 - Types with best possible out of the box support:
   - Any [value interface](https://github.com/OpenHFT/Chronicle-Values)
   - Any class implementing [`Byteable`](
   http://openhft.github.io/Chronicle-Bytes/apidocs/net/openhft/chronicle/bytes/Byteable.html)
   interface from [Chronicle Bytes](https://github.com/OpenHFT/Chronicle-Bytes)
   - Any class implementing [`BytesMarshallable`](
   http://openhft.github.io/Chronicle-Bytes/apidocs/net/openhft/chronicle/bytes/BytesMarshallable.html)
   interface from Chronicle Bytes. The implementation class should have a public no-arg constructor.
   - `byte[]` and `ByteBuffer`
   - `CharSequence`, `String` and `StringBuilder`. Note that these char sequence types are
   serialized using UTF-8 encoding by default. If you need a different encoding, refer to the
   example in the [custom `CharSequence` encoding](#custom-charsequence-encoding) section.
   - `Integer`, `Long` and `Double`

 - Types supported out of the box, but not particularly efficiently. You might want to implement
 more efficient [custom serializers](#custom-serializers) for them:
    - Any class implementing `java.io.Externalizable`. The implementation class should have a public
    no-arg constructor.
    - Any type implementing `java.io.Serializable`, including boxed primitive types (except listed
    above) and array types

 - Any other type, if [custom serializers](#custom-serializers) are provided.

https://github.com/OpenHFT/Chronicle-Values)[value interfaces] are preferred as they don't generate garbage, and have close to zero serialization/deserialization costs. They are preferable even to boxed primitives. For example, try to use `net.openhft.chronicle.core.values.IntValue` instead of `Integer`.

Generally, you must hint the `ChronicleMapBuilder` with the average sizes of the keys and values, which are going to be inserted into the `ChronicleMap`. This is needed to allocate the proper volume of the shared memory. Do this using `averageKey()` (preferred) or `averageKeySize()`, and
`averageValue()` or `averageValueSize()` respectively.

In the example above, `averageKey("Amsterdam")` is called, because it is assumed that "Amsterdam" (9 bytes in UTF-8 encoding) is the average length for city names; some names are shorter (Tokyo, 5 bytes), some names are longer (San Francisco, 13 bytes).

Another example could be if values in your `ChronicleMap` are adjacency lists of some social graph, where nodes are represented as `long` ids, and adjacency lists are `long[]` arrays. The average number of friends is 150. You could configure the `ChronicleMap` as follows:

```java
Map<Long, long[]> socialGraph = ChronicleMap
    .of(Long.class, long[].class)
    .name("social-graph-map")
    .entries(1_000_000_000L)
    .averageValue(new long[150])
    .create();
```

You could omit specifying key or value average sizes, if their types are boxed Java primitives or value interfaces. They are constantly-sized and Chronicle Map knows about that.

If the key or value type is constantly sized, or keys or values only of a certain size appear in your Chronicle Map domain, you should prefer to configure `constantKeySizeBySample()` or
`constantValueSizeBySample()`, instead of `averageKey()` or `averageValue()`. For example:

```java
ChronicleSet<UUID> uuids =
    ChronicleSet.of(UUID.class)
        .name("uuids")
        // All UUIDs take 16 bytes.
        .constantKeySizeBySample(UUID.randomUUID())
        .entries(1_000_000)
        .create();
```

=== Custom serializers

Chronicle Map allows you to configure custom marshallers for key or value types which are not supported out of the box. You can also serialize supported types like `String` in some custom way (encoded other than UTF-8), or serialize supported types more efficiently than by default.

There are three pairs of serialization interfaces, only one of them should be chosen in a single implementation, and supplied to the `ChronicleMapBuilder` for the key or value type. These are:

- link:CM_Tutorial_Bytes.adoc[BytesWriter and BytesReader]
- link:CM_Tutorial_Sized.adoc[SizedWriter and SizedReader]
- link:CM_Tutorial_DataAccess.adoc[DataAccess and SizedReader]

==== Custom serialization checklist

 1. Choose the most suitable pair of serialization interfaces; link:CM_Tutorial_Bytes.adoc[BytesWriter and BytesReader], link:CM_Tutorial_Sized.adoc[SizedWriter and SizedReader], or link:CM_Tutorial_DataAccess.adoc[DataAccess and SizedReader]. Recommendations on which pair to choose are given in
 the linked sections, describing each pair.

 2. If implementation of the writer or reader part is configuration-less, give it a `private`
 constructor, and define a single `INSTANCE` constant. A sole instance of this marshaller class in the JVM. Implement `ReadResolvable` and return `INSTANCE` from the `readResolve()` method. Do not make the implementation a Java `enum`.

 3. If both the writer and reader are configuration-less, merge them into a single `-Marshaller` implementation class.

 4. Make best efforts to reuse `using` objects on the reader side (`BytesReader` or `SizedReader`); including nesting objects.

 5. Make best efforts to cache intermediate serialization results on writer side while working with some object. For example, try not to make expensive computations in both `size()` and `write()` methods
 of the `SizedWriter` implementation. Rather, compute them and cache in an serializer instance
 field.

 6. Make best efforts to reuse intermediate objects that are used for reading or writing. Store them in instance fields of the serializer implementation.

 7. If a serializer implementation is stateful, or has cache fields, implement `StatefulCopyable`. +
  See link:CM_Tutorial_Understanding.adoc[Understanding `StatefulCopyable`] for more information.

 8. Implement `writeMarshallable()` and `readMarshallable()` by writing and reading configuration fields (but not the state or cache fields) of the serializer instance one-by-one. Use the given
 `WireOut`/`WireIn` object. +
 See [Custom `CharSequence` encoding](#custom-charsequence-encoding)
 section for some non-trivial example of implementing these methods. See also https://github.com/OpenHFT/Chronicle-Wire#using-wire[Wire tutorial].

 9. Don't forget to initialize transient/cache/state fileds of the instance in the end of
 `readMarshallable()` implementation. This is needed, because fefore calling `readMarshallable()`,
 Wire framework creates a serializer instance by means of `Unsafe.allocateInstance()` rather than
 calling any constructor.

 10. If implementing `DataAccess`, consider implementation to be `Data` also, and return `this` from
 `getData()` method.

 11. Don't forget to implement `equals()`, `hashCode()` and `toString()` in `Data` implementation,
 returned from `DataAccess.getData()` method, regardless if this is actually the same `DataAccess`
 object, or a separate object.

 12. Except `DataAccess` which is also a `Data`, serializers shouldn't override Object's `equals()`,
 `hashCode()` and `toString()` (these methods are never called on serializers inside Chronicle Map
 library); they shouldn't implement `Serializable` or `Externalizable` (but have to implement
 `net.openhft.chronicle.wire.Marshallable`); shouldn't implement `Cloneable` (but have to implement
 `StatefulCopyable`, if they are stateful or have cache fields).

 13. After implementing custom serializers, don't forget to actually apply them to
 `ChronicleMapBuilder` by `keyMarshallers()`, `keyReaderAndDataAccess()`, `valueMarshallers()` or
 `valueReaderAndDataAccess()` methods.

== `ChronicleMap` usage patterns

=== Single-key queries

First of all, `ChronicleMap` supports all operations from [`Map`](
https://docs.oracle.com/javase/8/docs/api/java/util/Map.html): `get()`, `put()`, etc, including
methods added in Java 8, like `compute()` and `merge()`, and [`ConcurrentMap`](
https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/ConcurrentMap.html) interfaces:
`putIfAbsent()`, `replace()`. All operations, including those which include "two steps", e. g.
`compute()`, are correctly synchronized in terms of `ConcurrentMap` interface.

This means, you could use `ChronicleMap` instance just like a `HashMap` or `ConcurrentHashMap`:

```java
PostalCodeRange amsterdamCodes = Values.newHeapInstance(PostalCodeRange.class);
amsterdamCodes.minCode(1011);
amsterdamCodes.maxCode(1183);
cityPostalCodes.put("Amsterdam", amsterdamCodes);

...

PostalCodeRange amsterdamCodes = cityPostalCodes.get("Amsterdam");
```

However, this approach often generates garbage, because the values should be deserialized from
off-heap memory to on-heap, the new value object are allocated. There are several possibilities to
reuse objects efficiently:

==== Value interfaces instead of boxed primitives

If you want to create a `ChronicleMap` where keys are `long` ids, use `LongValue` instead of `Long`
key:

```java
ChronicleMap<LongValue, Order> orders = ChronicleMap
    .of(LongValue.class, Order.class)
    .name("orders-map")
    .entries(1_000_000)
    .create();

LongValue key = Values.newHeapInstance(LongValue.class);
key.setValue(id);
orders.put(key, order);

...

long[] orderIds = ...
// Allocate a single heap instance for inserting all keys from the array.
// This could be a cached or ThreadLocal value as well, eliminating
// allocations altogether.
LongValue key = Values.newHeapInstance(LongValue.class);
for (long id : orderIds) {
    // Reuse the heap instance for each key
    key.setValue(id);
    Order order = orders.get(key);
    // process the order...
}
```

==== `chronicleMap.getUsing()`

Use `ChronicleMap#getUsing(K key, V using)` to reuse the value object. It works if:

 - The value type is `CharSequence`, pass `StringBuilder` as the `using` argument.
 For example:
 ```java
 ChronicleMap<LongValue, CharSequence> names = ...
 StringBuilder name = new StringBuilder();
 for (long id : ids) {
    key.setValue(id);
    names.getUsing(key, name);
    // process the name...
 }
 ```

 In this case, calling `names.getUsing(key, name)` is equivalent to
 ```java
 name.setLength(0);
 name.append(names.get(key));
 ```

 with the difference that it doesn't generate garbage.
 - The value type is value interface, pass heap instance to read the data into it without new object
 allocation:
 ```java
 ThreadLocal<PostalCodeRange> cachedPostalCodeRange =
    ThreadLocal.withInitial(() -> Values.newHeapInstance(PostalCodeRange.class));

 ...

 PostalCodeRange range = cachedPostalCodeRange.get();
 cityPostalCodes.getUsing(city, range);
 // process the range...
 ```
 - If the value type implements `BytesMarshallable`, or `Externalizable`, `ChronicleMap` attempts to
 reuse the given `using` object by deserializing the value into the given object.
 - If custom marshaller is configured in the `ChronicleMapBuilder` via `.valueMarshaller()`,
 `ChronicleMap` attempts to reuse the given object by calling `readUsing()` method from the
 marshaller interface.

If `ChronicleMap` fails to reuse the object in `getUsing()`, it makes no harm, it falls back to
object creation, like in `get()` method. In particular, even `null` is allowed to be passed as
`using` object. It allows "lazy" using object initialization pattern:
```java
// a field
PostalCodeRange cachedRange = null;

...

// in a method
cachedRange = cityPostalCodes.getUsing(city, cachedRange);
// process the range...
```
In this example, `cachedRange` is `null` initially, on the first `getUsing()` call the heap value
is allocated, and saved in a `cachedRange` field for later reuse.

<i>If the value type is a value interface, <b>don't</b> use flyweight implementation as `getUsing()`
argument.</i> This is dangerous, because on reusing flyweight points to the `ChronicleMap` memory
directly, but the access is not synchronized. At least you could read inconsistent value state,
at most - corrupt the `ChronicleMap` memory.

For accessing the `ChronicleMap` value memory directly use the following technique:

==== Working with an entry within a context

```java
try (ExternalMapQueryContext<CharSequence, PostalCodeRange, ?> c =
        cityPostalCodes.queryContext("Amsterdam")) {
    MapEntry<CharSequence, PostalCodeRange> entry = c.entry();
    if (entry != null) {
        PostalCodeRange range = entry.value().get();
        // Access the off-heap memory directly, by calling range
        // object getters.
        // This is very rewarding, when the value has a lot of fields
        // and expensive to copy to heap all of them, when you need to access
        // just a few fields.
    } else {
        // city not found..
    }
}
```

=== Multi-key queries

In this example, consistent graph edge addition and removals are implemented via multi-key queries:
```java
public static boolean addEdge(
        ChronicleMap<Integer, Set<Integer>> graph, int source, int target) {
    if (source == target)
        throw new IllegalArgumentException("loops are forbidden");
    ExternalMapQueryContext<Integer, Set<Integer>, ?> sourceC = graph.queryContext(source);
    ExternalMapQueryContext<Integer, Set<Integer>, ?> targetC = graph.queryContext(target);
    // order for consistent lock acquisition => avoid dead lock
    if (sourceC.segmentIndex() <= targetC.segmentIndex()) {
        return innerAddEdge(source, sourceC, target, targetC);
    } else {
        return innerAddEdge(target, targetC, source, sourceC);
    }
}

private static boolean innerAddEdge(
        int source, ExternalMapQueryContext<Integer, Set<Integer>, ?> sourceContext,
        int target, ExternalMapQueryContext<Integer, Set<Integer>, ?> targetContext) {
    try (ExternalMapQueryContext<Integer, Set<Integer>, ?> sc = sourceContext) {
        try (ExternalMapQueryContext<Integer, Set<Integer>, ?> tc = targetContext) {
            sc.updateLock().lock();
            tc.updateLock().lock();
            MapEntry<Integer, Set<Integer>> sEntry = sc.entry();
            if (sEntry != null) {
                MapEntry<Integer, Set<Integer>> tEntry = tc.entry();
                if (tEntry != null) {
                    return addEdgeBothPresent(sc, sEntry, source, tc, tEntry, target);
                } else {
                    addEdgePresentAbsent(sc, sEntry, source, tc, target);
                    return true;
                }
            } else {
                MapEntry<Integer, Set<Integer>> tEntry = tc.entry();
                if (tEntry != null) {
                    addEdgePresentAbsent(tc, tEntry, target, sc, source);
                } else {
                    addEdgeBothAbsent(sc, source, tc, target);
                }
                return true;
            }
        }
    }
}

private static boolean addEdgeBothPresent(
        MapQueryContext<Integer, Set<Integer>, ?> sc,
        @NotNull MapEntry<Integer, Set<Integer>> sEntry, int source,
        MapQueryContext<Integer, Set<Integer>, ?> tc,
        @NotNull MapEntry<Integer, Set<Integer>> tEntry, int target) {
    Set<Integer> sNeighbours = sEntry.value().get();
    if (sNeighbours.add(target)) {
        Set<Integer> tNeighbours = tEntry.value().get();
        boolean added = tNeighbours.add(source);
        assert added;
        sEntry.doReplaceValue(sc.wrapValueAsData(sNeighbours));
        tEntry.doReplaceValue(tc.wrapValueAsData(tNeighbours));
        return true;
    } else {
        return false;
    }
}

private static void addEdgePresentAbsent(
        MapQueryContext<Integer, Set<Integer>, ?> sc,
        @NotNull MapEntry<Integer, Set<Integer>> sEntry, int source,
        MapQueryContext<Integer, Set<Integer>, ?> tc, int target) {
    Set<Integer> sNeighbours = sEntry.value().get();
    boolean added = sNeighbours.add(target);
    assert added;
    sEntry.doReplaceValue(sc.wrapValueAsData(sNeighbours));

    addEdgeOneSide(tc, source);
}

private static void addEdgeBothAbsent(MapQueryContext<Integer, Set<Integer>, ?> sc, int source,
        MapQueryContext<Integer, Set<Integer>, ?> tc, int target) {
    addEdgeOneSide(sc, target);
    addEdgeOneSide(tc, source);
}

private static void addEdgeOneSide(MapQueryContext<Integer, Set<Integer>, ?> tc, int source) {
    Set<Integer> tNeighbours = new HashSet<>();
    tNeighbours.add(source);
    MapAbsentEntry<Integer, Set<Integer>> tAbsentEntry = tc.absentEntry();
    assert tAbsentEntry != null;
    tAbsentEntry.doInsert(tc.wrapValueAsData(tNeighbours));
}

public static boolean removeEdge(
        ChronicleMap<Integer, Set<Integer>> graph, int source, int target) {
    ExternalMapQueryContext<Integer, Set<Integer>, ?> sourceC = graph.queryContext(source);
    ExternalMapQueryContext<Integer, Set<Integer>, ?> targetC = graph.queryContext(target);
    // order for consistent lock acquisition => avoid dead lock
    if (sourceC.segmentIndex() <= targetC.segmentIndex()) {
        return innerRemoveEdge(source, sourceC, target, targetC);
    } else {
        return innerRemoveEdge(target, targetC, source, sourceC);
    }
}

private static boolean innerRemoveEdge(
        int source, ExternalMapQueryContext<Integer, Set<Integer>, ?> sourceContext,
        int target, ExternalMapQueryContext<Integer, Set<Integer>, ?> targetContext) {
    try (ExternalMapQueryContext<Integer, Set<Integer>, ?> sc = sourceContext) {
        try (ExternalMapQueryContext<Integer, Set<Integer>, ?> tc = targetContext) {
            sc.updateLock().lock();
            MapEntry<Integer, Set<Integer>> sEntry = sc.entry();
            if (sEntry == null)
                return false;
            Set<Integer> sNeighbours = sEntry.value().get();
            if (!sNeighbours.remove(target))
                return false;

            tc.updateLock().lock();
            MapEntry<Integer, Set<Integer>> tEntry = tc.entry();
            if (tEntry == null)
                throw new IllegalStateException("target node should be present in the graph");
            Set<Integer> tNeighbours = tEntry.value().get();
            if (!tNeighbours.remove(source))
                throw new IllegalStateException("the target node have an edge to the source");
            sEntry.doReplaceValue(sc.wrapValueAsData(sNeighbours));
            tEntry.doReplaceValue(tc.wrapValueAsData(tNeighbours));
            return true;
        }
    }
}
```

Usage:
```java
HashSet<Integer> averageValue = new HashSet<>();
for (int i = 0; i < AVERAGE_CONNECTIVITY; i++) {
    averageValue.add(i);
}
ChronicleMap<Integer, Set<Integer>> graph = ChronicleMapBuilder
        .of(Integer.class, (Class<Set<Integer>>) (Class) Set.class)
        .name("graph")
        .entries(100)
        .averageValue(averageValue)
        .create();

addEdge(graph, 1, 2);
removeEdge(graph, 1, 2);
```

== Close `ChronicleMap`
Unlike ConcurrentHashMap, ChronicleMap stores its data off heap, often in a memory mapped file.
Its recommended that you call close() once you have finished working with a ChronicleMap.

``` java
map.close()
```

This is especially important when working with ChronicleMap replication, as failure to call close may prevent
you from restarting a replicated map on the same port. In the event that your application crashes it may not
be possible to call close(). Your operating system will usually close dangling ports automatically,
so although it is recommended that you close() when you have finished with the map,
its not something that you must do, it's just something that we recommend you should do.

WARNING: *WARNING*. If you call `close()` too early before you have finished working with the map, this can cause
your JVM to crash. Close MUST BE the last thing that you do with the map.

== Behaviour Customization

You can customize the behaviour of Chronicle Map.

See <<CM_Tutorial_Behaviour.adoc#,CM_Tutorial_Behaviour.adoc>> for more details.


== Entry checksums

Chronicle Map 3 is able to store entry checksums along with entries. With entry checksums it is
possible to identify partially written entries (in case of operating system or power failure while)
and corrupted entries (in case of hardware memory or disk corruption) and clean them up during the <<CM_Tutorial.adoc#recovery,recovery>> procedure.

Entry checksums are 32-bit numbers, computed by a hash function with good avalanche effect.
Theoretically there is still about a one-billionth chance that after entry corruption it passes the
sum check.

By default, entry checksums are ON if the Chronicle Map is persisted to disk (i. e. created via
`createPersistedTo()` method), and OFF if the Chronicle Map is purely in-memory. Storing checksums
for a purely in-memory Chronicle Map hardly makes any practical sense, but you might want to disable
storing checksums for a persisted Chronicle Map by calling `.checksumEntries(false)` on the
`ChronicleMapBuilder` used to create a map. It makes sense if you don't need extra safety checksums
provide.

Entry checksums are computed automatically when an entry is inserted into a Chronicle Map, and
re-computed automatically on operations which update the whole value, e. g. `map.put()`,
`map.replace()`, `map.compute()`, `mapEntry.doReplaceValue()` (See `MapEntry` interface in
[Javadocs](http://www.javadoc.io/doc/net.openhft/chronicle-map/). But if you update values directly,
bypassing Chronicle Map logic, keeping entry checksum up-to-date is also your responsibility.

It is strongly recommended to update off-heap memory of values directly only within a
[context](#working-with-an-entry-within-a-context-section) and update or write lock held. Within a
context, you are provided with an entry object of `MapEntry` type. To re-compute entry checksum
manually, cast that object to `ChecksumEntry` type and call `.updateChecksum()` method on it:

``` java
try (ChronicleMap<Integer, LongValue> map = ChronicleMap
        .of(Integer.class, LongValue.class)
        .entries(1)
        // Entry checksums make sense only for persisted Chronicle Maps, and are ON by
        // default for such maps
        .createPersistedTo(file)) {

    LongValue value = Values.newHeapInstance(LongValue.class);
    value.setValue(42);
    map.put(1, value);

    try (ExternalMapQueryContext<Integer, LongValue, ?> c = map.queryContext(1)) {
        // Update lock required for calling ChecksumEntry.checkSum()
        c.updateLock().lock();
        MapEntry<Integer, LongValue> entry = c.entry();
        Assert.assertNotNull(entry);
        ChecksumEntry checksumEntry = (ChecksumEntry) entry;
        Assert.assertTrue(checksumEntry.checkSum());

        // to access off-heap bytes, should call value().getUsing() with Native value
        // provided. Simple get() return Heap value by default
        LongValue nativeValue =
                entry.value().getUsing(Values.newNativeReference(LongValue.class));
        // This value bytes update bypass Chronicle Map internals, so checksum is not
        // updated automatically
        nativeValue.setValue(43);
        Assert.assertFalse(checksumEntry.checkSum());

        // Restore correct checksum
        checksumEntry.updateChecksum();
        Assert.assertTrue(checksumEntry.checkSum());
    }
}
```

'''
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