Elasticsearch offers near-real-time analytics and search for many kinds of data. No matter what kind of data you have—numerical, geographical, or structured—Elasticsearch can effectively store and index it to enable quick searches.

What is Elasticsearch?

Elasticsearch is written in Java and is dual-licensed under the (source-available) Server Side Public License and the Elastic license, with some components falling under the proprietary (source-available) Elastic License. Official clients are available for Java,.NET (C#), PHP, Python, Ruby, and other languages. According to the DB-Engines rankings, Elasticsearch is the most popular enterprise search engine.

Types of Elasticsearch Problems

• Discovery and Cluster Formation: This category addresses challenges during the discovery phase when nodes must communicate to form a cluster.
• Indexing Data and Sharding: This covers concerns with index settings and mapping, but because these are covered in prior courses, we’ll only discuss how sharding issues are represented in the cluster state.
• Search: Search, as the final phase in the setup process, might cause issues with searches that yield less relevant results or with search performance.
• Node Setup: Installation and first startup are both potential concerns. The challenges can vary greatly depending on how you run your cluster (e.g., whether it’s a local installation, operating on containers, or via a cloud service).

Troubleshooting Common Problems of Elasticsearch

Docker Connection Refused

The DXP container recognizes the Elasticsearch IP to establish a connection and add ‘/etc/hosts/‘ entries that map the Elasticsearch container name to the Elasticsearch server host IP address during the docker run phase by passing an argument like this:

--add-host elasticsearch:[IP address]

Output:

Output

Disable Elasticsearch Deprecation Logging

Sometimes the Elasticsearch APIs used in Liferay’s Elasticsearch connections are deprecated. Even if there is no impact on the functionality required by Liferay, warning log entries may result:

docker run --add-host elasticsearch:192.168.0.00 my_image

Output:

Output

Cluster Health is Yellow or Red

Not all main and replica shards have been assigned, as indicated by the cluster health state of yellow or red. Causes include:

• Insufficient data nodes to distribute all shards.
• Nodes are inaccessible or have failed.
• Shard allocation is hindered by awareness settings or allocation filters.

Check cluster health and shards:

curl -X GET "localhost:9300/_cluster/health?pretty"
curl -X GET "localhost:9300/_cat/shards?v"

Output:

Output

Slow Query Performance

Results from queries are returned slowly and take longer than anticipated. You must examine and improve the sluggish inquiries.

Enable slow query logging:

# Enable slow query logging
curl -X PUT "localhost:9200/_cluster/settings" -H 'Content-Type: application/json' -d'
{
  "transient": {
    "logger.index.search.slowlog": "TRACE"
  }
}'

# Check slow log
tail -f /var/log/elasticsearch/elasticsearch_index_search_slowlog.log

Output:

Output

Index Creation Error

When attempting to build a new index, an error occurs. This can happen due to:

• Name conflicts.
• Insufficient permissions.
• Invalid index settings.

Create an index with settings:

# Create an index with settings
curl -X PUT "localhost:9300/new_index" -H 'content-type: application/json'
{
  "settings": {
    "number_of_shards": 3,
    "number_of_replicas": 1
  },
  "mappings": {
    "properties": {
      "field1": {
        "type": "text"
      }
    }
  }
}'

Output:

Output

Best Practices for Troubleshooting Common Elasticsearch Problems

Monitor Cluster Health

• Regularly monitor cluster health using the ‘_cluster/health' API.
• Use tools like Kibana or third-party monitoring solutions to get alerts and visual insights.

Log Management

• Enable and review Elasticsearch logs (‘elasticsearch.log', ‘gc.log', and slow logs) to detect issues early.
• Use centralized logging solutions to aggregate and analyze logs across your cluster.

Profile and Optimize Queries

• Use the ‘_profile' API to identify and optimize slow queries.
• Utilize filters for frequently used queries to take advantage of caching.

Manage Shards and Replicas

• Ensure that you have an appropriate number of shards and replicas for your data size and use case.
• Rebalance shards if nodes are unevenly loaded using the ‘_cluster/reroute' API.

Tune JVM Settings

• Allocate sufficient heap size (not more than 50% of total RAM) in jvm.options.
• Monitor and adjust garbage collection settings to prevent full GCs and OutOfMemory errors.

Conclusion

In this article, we covered common Elasticsearch problems, from cluster health issues to slow query performance and indexing errors. Elasticsearch is a powerful but complex tool, and its complexity increases when managing multiple instances in a cluster. Proper troubleshooting and optimization are crucial for maintaining a healthy Elasticsearch environment. By addressing these common issues, you can ensure efficient and reliable search and analytics capabilities for your data.