OpenSearch/docs/reference/indices/split-index.asciidoc

[[indices-split-index]]
== Split Index

The split index API allows you to split an existing index into a new index,
where each original primary shard is split into two or more primary shards in
the new index.

The number of times the index can be split (and the number of shards that each
original shard can be split into) is determined by the
`index.number_of_routing_shards` setting. The number of routing shards
specifies the hashing space that is used internally to distribute documents
across shards with consistent hashing. For instance, a 5 shard index with
`number_of_routing_shards` set to `30` (`5 x 2 x 3`) could be split by a
factor of `2` or `3`.  In other words, it could be split as follows:

* `5` -> `10` -> `30`  (split by 2, then by 3)
* `5` -> `15` -> `30` (split by 3, then by 2)
* `5` -> `30` (split by 6)

While you can set the `index.number_of_routing_shards` setting explicitly at
index creation time, the default value depends upon the number of primary
shards in the original index.  The default is designed to allow you to split
by factors of 2 up to a maximum of 1024 shards.  However, the original number
of primary shards must taken into account.  For instance, an index created
with 5 primary shards could be split into 10, 20, 40, 80, 160, 320, or a
maximum of 740 shards (with a single split action or multiple split actions).

If the original index contains one primary shard (or a multi-shard index has
been <<indices-shrink-index,shrunk>> down to a single primary shard), then the
index may by split into an arbitrary number of shards greater than 1.  The
properties of the default number of routing shards will then apply to the
newly split index.

[float]
=== How does splitting work?

Splitting works as follows:

* First, it creates a new target index with the same definition as the source
  index, but with a larger number of primary shards.

* Then it hard-links segments from the source index into the target index. (If
  the file system doesn't support hard-linking, then all segments are copied
  into the new index, which is a much more time consuming process.)

* Once the low level files are created all documents will be `hashed` again to delete
  documents that belong to a different shard.

* Finally, it recovers the target index as though it were a closed index which
  had just been re-opened.

[float]
=== Why doesn't Elasticsearch support incremental resharding?

Going from `N` shards to `N+1` shards, aka. incremental resharding, is indeed a
feature that is supported by many key-value stores. Adding a new shard and
pushing new data to this new shard only is not an option: this would likely be
an indexing bottleneck, and figuring out which shard a document belongs to
given its `_id`, which is necessary for get, delete and update requests, would
become quite complex. This means that we need to rebalance existing data using
a different hashing scheme.

The most common way that key-value stores do this efficiently is by using
consistent hashing. Consistent hashing only requires `1/N`-th of the keys to
be relocated when growing the number of shards from `N` to `N+1`. However
Elasticsearch's unit of storage, shards, are Lucene indices. Because of their
search-oriented data structure, taking a significant portion of a Lucene index,
be it only 5% of documents, deleting them and indexing them on another shard
typically comes with a much higher cost than with a key-value store. This cost
is kept reasonable when growing the number of shards by a multiplicative factor
as described in the above section: this allows Elasticsearch to perform the
split locally, which in-turn allows to perform the split at the index level
rather than reindexing documents that need to move, as well as using hard links
for efficient file copying.

In the case of append-only data, it is possible to get more flexibility by
creating a new index and pushing new data to it, while adding an alias that
covers both the old and the new index for read operations. Assuming that the
old and new indices have respectively +M+ and +N+ shards, this has no overhead
compared to searching an index that would have +M+N+ shards.

[float]
=== Preparing an index for splitting

Create a new index:

[source,js]
--------------------------------------------------
PUT my_source_index?include_type_name=true
{
  "settings": {
    "index.number_of_shards" : 1
  }
}
-------------------------------------------------
// CONSOLE

In order to split an index, the index must be marked as read-only,
and have <<cluster-health,health>> `green`.

This can be achieved with the following request:

[source,js]
--------------------------------------------------
PUT /my_source_index/_settings
{
  "settings": {
    "index.blocks.write": true <1>
  }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

<1> Prevents write operations to this index while still allowing metadata
    changes like deleting the index.

[float]
=== Splitting an index

To split `my_source_index` into a new index called `my_target_index`, issue
the following request:

[source,js]
--------------------------------------------------
POST my_source_index/_split/my_target_index
{
  "settings": {
    "index.number_of_shards": 2
  }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

The above request returns immediately once the target index has been added to
the cluster state -- it doesn't wait for the split operation to start.

[IMPORTANT]
=====================================

Indices can only be split if they satisfy the following requirements:

* the target index must not exist

* The source index must have fewer primary shards than the target index.

* The number of primary shards in the target index must be a factor of the
  number of primary shards in the source index.

* The node handling the split process must have sufficient free disk space to
  accommodate a second copy of the existing index.

=====================================

The `_split` API is similar to the <<indices-create-index, `create index` API>>
and accepts `settings` and `aliases` parameters for the target index:

[source,js]
--------------------------------------------------
POST my_source_index/_split/my_target_index
{
  "settings": {
    "index.number_of_shards": 5 <1>
  },
  "aliases": {
    "my_search_indices": {}
  }
}
--------------------------------------------------
// CONSOLE
// TEST[s/^/PUT my_source_index\n{"settings": {"index.blocks.write": true, "index.number_of_shards": "1"}}\n/]

<1> The number of shards in the target index. This must be a factor of the
    number of shards in the source index.


NOTE: Mappings may not be specified in the `_split` request.

[float]
=== Monitoring the split process

The split process can be monitored with the <<cat-recovery,`_cat recovery`
API>>, or the <<cluster-health, `cluster health` API>> can be used to wait
until all primary shards have been allocated by setting the  `wait_for_status`
parameter to `yellow`.

The `_split` API returns as soon as the target index has been added to the
cluster state, before any shards have been allocated. At this point, all
shards are in the state `unassigned`. If, for any reason, the target index
can't be allocated, its primary shard will remain `unassigned` until it
can be allocated on that node.

Once the primary shard is allocated, it moves to state `initializing`, and the
split process begins. When the split operation completes, the shard will
become `active`. At that  point, Elasticsearch will try to allocate any
replicas and may decide to relocate the primary shard to another node.

[float]
=== Wait For Active Shards

Because the split operation creates a new index to split the shards to,
the <<create-index-wait-for-active-shards,wait for active shards>> setting
on index creation applies to the split index action as well.