Understanding Shards

Elasticsearch indexes can grow to enormous sizes, making data management challenging. To handle this, an index is divided into smaller units called shards. Each shard is a separate Apache Lucene index, containing a subset of the documents from the main Elasticsearch index. This division helps keep resource usage in check, as Lucene indexes have a maximum document limit of approximately 2.1 billion.

Large shards can be inefficient, making operations like moving indices across machines time-consuming and resource-intensive. Splitting data across multiple shards distributed across different machines allows for manageable chunks, reducing risks and improving efficiency. However, finding the right balance in the number of shards is crucial. Too few shards can slow down query execution, while too many can consume excessive memory and disk space, impacting performance.

Setting Up Shards

When creating an index, you define the number of shards, a decision that cannot be changed without reindexing the data. For instance, you might set up an index as follows:

PUT /sensor
{
    "settings": {
        "index": {
            "number_of_shards": 6,
            "number_of_replicas": 2
        }
    }
}

Generally, each shard should hold between 30-50GB of data. For example, if you expect to accumulate around 300GB of logs daily, an index with 10 shards would be appropriate.

Shard States

Shards can exist in various states:

• Initializing: The initial state before the shard becomes usable.
• Started: The shard is active and ready to receive requests.
• Relocating: The shard is being moved to another node, often due to disk space issues.
• Unassigned: The shard has not been assigned, typically due to node failure or index restoration.

To view shard states and metadata, use the following command:

GET _cat/shards

For specific indices:

GET _cat/shards/sensor

Elasticsearch, built on top of Apache Lucene, offers a powerful distributed system that enhances scalability and fault tolerance. This distributed nature introduces complexity, with various factors influencing performance and stability.

Key among these are shards and replicas, fundamental components that require careful management to maintain an efficient Elasticsearch cluster. This article delves into what shards and replicas are, their impact, and the tools available to optimize their configuration.