Elasticsearch中,在node的配置中可以指定path.data
用来作为节点数据的存储目录,而且我们可以指定多个值来作为数据存储的路径,那么Elasticsearch是如何判断应该存储到哪个路径下呢?今天我就记录一下这个问题。
Elasticsearch的索引创建过程
- 集群master收到创建索引的请求后,经过创建索引的一些步骤,最终会将索引创建完成的请求提交到ClusterState
- master将根据ClusterState分发给所有节点
- 涉及创建shard的节点会读取本地可用的
path.data
,然后依据一定的规则获取路径。 - 创建基本shard路径,保存基本的shard信息。
如何确定在哪个目录下
源码
主要调用的是ShardPath的selectNewPathForShard方法
for (NodeEnvironment.NodePath nodePath : env.nodePaths()) {
totFreeSpace = totFreeSpace.add(BigInteger.valueOf(nodePath.fileStore.getUsableSpace()));
}
// TODO: this is a hack!! We should instead keep track of incoming (relocated) shards since we know
// how large they will be once they're done copying, instead of a silly guess for such cases:
// Very rough heuristic of how much disk space we expect the shard will use over its lifetime, the max of current average
// shard size across the cluster and 5% of the total available free space on this node:
BigInteger estShardSizeInBytes = BigInteger.valueOf(avgShardSizeInBytes).max(totFreeSpace.divide(BigInteger.valueOf(20)));
// TODO - do we need something more extensible? Yet, this does the job for now...
final NodeEnvironment.NodePath[] paths = env.nodePaths();
// If no better path is chosen, use the one with the most space by default
NodeEnvironment.NodePath bestPath = getPathWithMostFreeSpace(env);
if (paths.length != 1) {
Map<NodeEnvironment.NodePath, Long> pathToShardCount = env.shardCountPerPath(shardId.getIndex());
// Compute how much space there is on each path
final Map<NodeEnvironment.NodePath, BigInteger> pathsToSpace = new HashMap<>(paths.length);
for (NodeEnvironment.NodePath nodePath : paths) {
FileStore fileStore = nodePath.fileStore;
BigInteger usableBytes = BigInteger.valueOf(fileStore.getUsableSpace());
pathsToSpace.put(nodePath, usableBytes);
}
bestPath = Arrays.stream(paths)
// Filter out paths that have enough space
.filter((path) -> pathsToSpace.get(path).subtract(estShardSizeInBytes).compareTo(BigInteger.ZERO) > 0)
// Sort by the number of shards for this index
.sorted((p1, p2) -> {
int cmp = Long.compare(pathToShardCount.getOrDefault(p1, 0L),
pathToShardCount.getOrDefault(p2, 0L));
if (cmp == 0) {
// if the number of shards is equal, tie-break with the number of total shards
cmp = Integer.compare(dataPathToShardCount.getOrDefault(p1.path, 0),
dataPathToShardCount.getOrDefault(p2.path, 0));
if (cmp == 0) {
// if the number of shards is equal, tie-break with the usable bytes
cmp = pathsToSpace.get(p2).compareTo(pathsToSpace.get(p1));
}
}
return cmp;
})
// Return the first result
.findFirst()
// Or the existing best path if there aren't any that fit the criteria
.orElse(bestPath);
}
statePath = bestPath.resolve(shardId);
dataPath = statePath;
}
过程分析
- 首先判断是否自定义了
path.data
,没有自定义就在默认路径下创建 - 自定义的情况下确保节点下最少有5%的空间可以使用
- 获取所有的paths,
- 然后设置默认最佳的path是当前拥有最多空间的path
- 遍历所有的paths,首先过滤掉没有空间的path,如果最终没有符合的,就返回4步骤的path,否则继续6步骤
- 按照规则对paths排序,首先判断每个path下该索引的shard数,优先返回含有本索引的shard数最少的path;
当条件结果相同,对比每个path中包含有的shard总数(所有索引的),返回包含shard数最少的path;
当2条件结果相同,对比可用空间,返回可用空间最大的path - 生成相应的路径,创建目录等信息。