How to Reindex Data in Amazon OpenSearch Serverless Using Amazon OpenSearch Ingestion | AWS Guide

# How to Reindex Data in Amazon OpenSearch Serverless Using Amazon OpenSearch Ingestion | AWS Guide

Amazon OpenSearch Service, formerly known as Amazon Elasticsearch Service, is a managed service that makes it easy to deploy, operate, and scale OpenSearch clusters in the AWS Cloud. With the advent of Amazon OpenSearch Serverless, users can now enjoy a more streamlined and cost-effective way to manage their search and analytics workloads without worrying about the underlying infrastructure. One of the critical tasks in managing OpenSearch data is reindexing, which involves copying data from one index to another. This article will guide you through the process of reindexing data in Amazon OpenSearch Serverless using Amazon OpenSearch Ingestion.

## What is Reindexing?

Reindexing is the process of copying data from one index to another within an OpenSearch cluster. This is often necessary when you need to:

– Change the mapping of an index.
– Upgrade to a new version of OpenSearch.
– Optimize performance by restructuring your data.
– Migrate data between clusters.

## Prerequisites

Before you start reindexing data, ensure you have the following:

1. **Amazon OpenSearch Serverless Domain**: An active OpenSearch Serverless domain where your source and target indexes reside.
2. **AWS CLI**: The AWS Command Line Interface installed and configured on your local machine.
3. **IAM Permissions**: Appropriate IAM permissions to access and manage your OpenSearch Serverless domain and Amazon OpenSearch Ingestion.

## Step-by-Step Guide to Reindex Data

### Step 1: Set Up Amazon OpenSearch Ingestion

Amazon OpenSearch Ingestion is a fully managed service that allows you to ingest and transform data before indexing it into your OpenSearch domain. To set up Amazon OpenSearch Ingestion:

1. **Create an Ingestion Pipeline**:
– Navigate to the Amazon OpenSearch Service console.
– Select “Ingestion Pipelines” from the left-hand menu.
– Click “Create pipeline” and configure the pipeline settings, including source and destination details.

2. **Configure Source and Destination**:
– Define the source index from which data will be read.
– Specify the destination index where the reindexed data will be stored.

### Step 2: Create a Reindexing Script

You can use a Python script with the `requests` library to perform the reindexing operation. Below is an example script:

“`python
import requests
from requests.auth import HTTPBasicAuth

# Replace these variables with your own values
source_index = ‘source-index’
destination_index = ‘destination-index’
opensearch_endpoint = ‘https://your-opensearch-endpoint’
username = ‘your-username’
password = ‘your-password’

# Reindex API endpoint
reindex_url = f'{opensearch_endpoint}/_reindex’

# Reindex payload
payload = {
“source”: {
“index”: source_index
},
“dest”: {
“index”: destination_index
}
}

# Perform the reindexing operation
response = requests.post(reindex_url, json=payload, auth=HTTPBasicAuth(username, password))

if response.status_code == 200:
print(“Reindexing started successfully.”)
else:
print(f”Failed to start reindexing: {response.text}”)
“`

### Step 3: Monitor the Reindexing Process

Once the reindexing operation has started, you can monitor its progress using the `_tasks` API:

“`python
tasks_url = f'{opensearch_endpoint}/_tasks?detailed=true&actions=*reindex’
response = requests.get(tasks_url, auth=HTTPBasicAuth(username, password))

if response.status_code == 200:
print(“Reindexing tasks:”)
print(response.json())
else:
print(f”Failed to retrieve tasks: {response.text}”)
“`

### Step 4: Verify the Reindexed Data

After the reindexing process is complete, verify that the data has been correctly copied to the destination index:

1. **Check Document Count**:
– Compare the document count between the source and destination indexes using the `_count` API.

2. **Query Data**:
– Perform sample queries on both indexes to ensure data integrity and consistency.

### Step 5: Clean Up

Once you have verified that the reindexed data is correct, you can clean up any temporary resources or indexes that are no longer needed.

## Conclusion

Reindexing data in Amazon OpenSearch Serverless using Amazon OpenSearch Ingestion is a straightforward process that involves setting up an ingestion pipeline, creating a reindexing script, monitoring the process, and verifying the results. By following this guide, you can efficiently manage your OpenSearch data and ensure optimal performance for your search and analytics workloads.

For more detailed information, refer to the official [Amazon OpenSearch Service documentation](https://docs

• Source Link: https://zephyrnet.com/perform-reindexing-in-amazon-opensearch-serverless-using-amazon-opensearch-ingestion-amazon-web-services/