Segment replication

Segment replication involves copying segment files across shards instead of indexing documents on each shard copy. This approach enhances indexing throughput and reduces resource utilization but increases network utilization. Segment replication is the first feature in a series of features designed to decouple reads and writes in order to lower compute costs.

When the primary shard sends a checkpoint to replica shards on a refresh, a new segment replication event is triggered on replica shards. This happens:

• When a new replica shard is added to a cluster.
• When there are segment file changes on a primary shard refresh.
• During peer recovery, such as replica shard recovery and shard relocation (explicit allocation using the move allocation command or automatic shard rebalancing).

Use cases

Segment replication can be applied in a variety of scenarios, including:

• High write loads without high search requirements and with longer refresh times.
• When experiencing very high loads, you want to add new nodes but don’t want to index all data immediately.
• OpenSearch cluster deployments with low replica counts, such as those used for log analytics.

Remote-backed storage

As of OpenSearch 2.10, you can use two methods for segment replication:

• Remote-backed storage, a persistent storage solution: The primary shard sends segment files to the remote-backed storage, and the replica shards source the copy from the same store. For more information about using remote-backed storage, see Remote-backed storage.
• Node-to-node communication: The primary shard sends segment files directly to the replica shards using node-to-node communication.

Segment replication configuration

Setting the default replication type for a cluster affects all newly created indexes. You can, however, specify a different replication type when creating an index. Index-level settings override cluster-level settings.

Creating an index with segment replication

To use segment replication as the replication strategy for an index, create the index with the replication.type parameter set to SEGMENT as follows:

PUT /my-index1
{
  "settings": {
    "index": {
      "replication.type": "SEGMENT" 
    }
  }
}

If you’re using remote-backed storage, add the remote_store property to the index request body.

When using node-to-node replication, the primary shard consumes more network bandwidth because it pushes segment files to all the replica shards. Thus, it’s beneficial to distribute primary shards equally between the nodes. To ensure balanced primary shard distribution, set the dynamic cluster.routing.allocation.balance.prefer_primary setting to true. For more information, see Cluster settings.

For the best performance, it is recommended that you enable the following settings:

1. Segment replication backpressure
2. Balanced primary shard allocation, using the following command:

curl -X PUT "$host/_cluster/settings?pretty" -H 'Content-Type: application/json' -d'
  {
    "persistent": {
    "cluster.routing.allocation.balance.prefer_primary": true,
    "segrep.pressure.enabled": true
   }
  }

Setting the replication type for a cluster

You can set the default replication type for newly created cluster indexes in the opensearch.yml file as follows:

cluster.indices.replication.strategy: 'SEGMENT'

Creating an index with document replication

Even when the default replication type is set to segment replication, you can create an index that uses document replication by setting replication.type to DOCUMENT as follows:

PUT /my-index1
{
  "settings": {
    "index": {
      "replication.type": "DOCUMENT" 
    }
  }
}

Considerations

When using segment replication, consider the following:

1. Enabling segment replication for an existing index requires reindexing.
2. Cross-cluster replication does not currently use segment replication to copy between clusters.
3. Segment replication is not compatible with document-level monitors, which are used with the Alerting and Security Analytics plugins. The plugins also use the latest available data on replica shards when using the immediate refresh policy, and segment replication can delay the policy’s availability, resulting in stale replica shards.
4. Segment replication leads to increased network congestion on primary shards using node-to-node replication because replica shards fetch updates from the primary shard. With remote-backed storage, the primary shard can upload segments to, and the replicas can fetch updates from, the remote-backed storage. This helps offload responsibilities from the primary shard to the remote-backed storage. Read-after-write guarantees: Segment replication does not currently support setting the refresh policy to wait_for. If you set the refresh query parameter to wait_for and then ingest documents, you’ll get a response only after the primary node has refreshed and made those documents searchable. Replica shards will respond only after having written to their local translog. If real-time reads are needed, consider using the get or mget API operations.
5. As of OpenSearch 2.10, system indexes support segment replication.
6. Get, MultiGet, TermVector, and MultiTermVector requests serve strong reads by routing requests to the primary shards. Routing more requests to the primary shards may degrade performance as compared to distributing requests across primary and replica shards. To improve performance in read-heavy clusters, we recommend setting the realtime parameter in these requests to false. For more information, see Issue #8700.

Benchmarks

During initial benchmarks, segment replication users reported 40% higher throughput than when using document replication with the same cluster setup.

The following benchmarks were collected with OpenSearch-benchmark using the stackoverflow and nyc_taxi datasets.

The benchmarks demonstrate the effect of the following configurations on segment replication:

• The workload size
• The number of primary shards
• The number of replicas

Your results may vary based on the cluster topology, hardware used, shard count, and merge settings.

Increasing the workload size

The following table lists benchmarking results for the nyc_taxi dataset with the following configuration:

• 10 m5.xlarge data nodes
• 40 primary shards, 1 replica each (80 shards total)
• 4 primary shards and 4 replica shards per node

As the size of the workload increases, the benefits of segment replication are amplified because the replicas are not required to index the larger dataset. In general, segment replication leads to higher throughput at lower resource costs than document replication in all cluster configurations, not accounting for replication lag.

Increasing the number of primary shards

The following table lists benchmarking results for the nyc_taxi dataset for 40 and 100 primary shards.

As the number of primary shards increases, the benefits of segment replication over document replication decrease. While segment replication is still beneficial with a larger number of primary shards, the difference in performance becomes less pronounced because there are more primary shards per node that must copy segment files across the cluster.

Increasing the number of replicas

The following table lists benchmarking results for the stackoverflow dataset for 1 and 9 replicas.

As the number of replicas increases, the amount of time required for primary shards to keep replicas up to date (known as the replication lag) also increases. This is because segment replication copies the segment files directly from primary shards to replicas.

The benchmarking results show a non-zero error rate as the number of replicas increases. The error rate indicates that the segment replication backpressure mechanism is initiated when replicas cannot keep up with the primary shard. However, the error rate is offset by the significant CPU and memory gains that segment replication provides.

Next steps

1. Track future enhancements to segment replication.
2. Read this blog post about segment replication.

Related articles

• Segment replication backpressure