Elasticsearch中fielddata_cache的实现

简书地址

背景

    基于一次fielddata_cache(容量还没到阈值)被逐出后，想具体了解fielddata_cache的实现来判断fielddata数据是否是常驻内存亦或是只是个软、弱引用，本文基于v1.0.0版本。

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实现

    我们直接从Elasticsearch.java这个启动类开始往下看：

Elasticsearch.java {
    public static void main(String[] args) {
        Bootstrap.main(args);
    }
}

    Elasticsearch通过Bootstrap类来启动，具体再看Bootstrap的实现，忽略一些代码，我们来Bootstrap的实例化和初始化：

Bootstrap.java {
    public static void main(String[] args) {

        bootstrap = new Bootstrap();

        Tuple tuple = null; //我们的一些配置
        try {
            tuple = initialSettings();
            setupLogging(tuple);
        } catch (Exception e) {
            ...
        }

        try {

            bootstrap.setup(true, tuple);

            ...
        } catch (Throwable e) {
                ...
        }
    }
}

    Bootstrap的setup()会创建我们的Elasticsearch的节点实例：

Bootstrap.java {

    private Node node;

    private void setup(boolean addShutdownHook, Tuple tuple) throws Exception {

        NodeBuilder nodeBuilder = NodeBuilder.nodeBuilder().settings(tuple.v1()).loadConfigSettings(false);
        node = nodeBuilder.build();
        ...       
    }

}

    NodeBuilder会创建一个InternalNode实例，我们InternalNode的初始化，重点看到我们会添加一个IndicesModule：

InternalNode.java {

    public InternalNode(Settings pSettings, boolean loadConfigSettings) throws ElasticsearchException {

        logger.info("initializing ...");

        ...

        ModulesBuilder modules = new ModulesBuilder();

        modules.add(new IndicesModule(settings));

        ...

        logger.info("initialized");
    }
}

    再接着看IndicesModule的实现，我们通过绑定IndicesFieldDataCache类来实现索引级别的fielddata_cache：

IndicesModule.java {

    protected void configure() {
        ...
        bind(IndicesFieldDataCache.class).asEagerSingleton();
        ...
    }
}

    重点来看IndicesFieldDataCache的实现，从下面代码可以看到Elasticsearch通过guava的CacheBuilder来实现索引级别的fielddata_cache，具体的CacheBuilder介绍可以自行查阅一下：

IndicesFieldDataCache.java {

    Cache cache;

    private volatile String size;
    private volatile long sizeInBytes;
    private volatile TimeValue expire;

    @Inject
    public IndicesFieldDataCache(Settings settings) {
        super(settings);
        this.size = componentSettings.get("size", "-1"); //indices.fielddata.cache.size的大小
        this.sizeInBytes = componentSettings.getAsMemory("size", "-1").bytes(); //indices.fielddata.cache.size的大小
        this.expire = componentSettings.getAsTime("expire", null); //indices.fielddata.cache.expire的大小
        buildCache();
    }

    private void buildCache() {
        CacheBuilder cacheBuilder = CacheBuilder.newBuilder()
                .removalListener(this);
        if (sizeInBytes > 0) { //设置LRU的阈值
            cacheBuilder.maximumWeight(sizeInBytes).weigher(new FieldDataWeigher());
        }

        cacheBuilder.concurrencyLevel(16);
        if (expire != null && expire.millis() > 0) { //设置Cache的过期时间
            cacheBuilder.expireAfterAccess(expire.millis(), TimeUnit.MILLISECONDS);
        }
        logger.debug("using size [{}] [{}], expire [{}]", size, new ByteSizeValue(sizeInBytes), expire);
        cache = cacheBuilder.build();
    }

    ...
} 

    最后再看CacheBuilder是怎么被使用的(默认情况下CacheBuilder的key和value都是强引用的)，IndicesFieldDataCache在给上层提供实现时是返回了一个IndexFieldCache，可以看到在需要load索引的fielddata_cache时通过CacheBuilder在get时候的原则”获取缓存-如果没有-则计算”实现:

IndexFieldCache.java {

    @Nullable
    private final IndexService indexService;
    final Index index;
    final FieldMapper.Names fieldNames;
    final FieldDataType fieldDataType;

    IndexFieldCache(@Nullable IndexService indexService, Index index, FieldMapper.Names fieldNames, FieldDataType fieldDataType) {
        this.indexService = indexService;
        this.index = index;
        this.fieldNames = fieldNames;
        this.fieldDataType = fieldDataType;
    }

    @Override
    public > FD load(final AtomicReaderContext context, final IFD indexFieldData) throws Exception {
        final Key key = new Key(this, context.reader().getCoreCacheKey());

        return (FD) cache.get(key, new Callable() {
            @Override
            public AtomicFieldData call() throws Exception {
                SegmentReaderUtils.registerCoreListener(context.reader(), IndexFieldCache.this);
                AtomicFieldData fieldData = indexFieldData.loadDirect(context);

                ...

                return fieldData;
            }
        });
    }

}

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总结

    简单介绍了Elasticsearch-1.0.0版本fielddata_cache的实现，经过分析知道fielddata_cache默认是强引用对象，所以只存在LRU并不会被GC掉。

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(个人分析，有错误请指正)