
# Reindexing Search

If you are encountering any of the following issues:

- Mismatch in counts of Data Assets.
- Data not appearing.
- Errors such as `shards_exception`.
- Problems with the search mechanism.
- Empty results in the Explore section.
- Missing lineage information.

Perform the reindexing process described below.

### Reindex

{% partial file="/v1.6/deployment/reindex.md" /%}

**Note:** If you continue to experience issues, consider `re-installing` the search application.

## Configuration Parameters for Reindexing

This document provides detailed descriptions and best practices for configuring the reindexing process parameters. Proper configuration ensures efficient and reliable reindexing while minimizing potential system bottlenecks.

{% image
src="/images/v1.6/deployment/upgrade/reindex.png"
alt="Reindex Configuration"
/%}

### 1. `recreateIndex`
**Description**:  
Determines whether to recreate the index from scratch during the reindexing process. Setting this to `true` will drop the existing index and create a new one.  

**Best Practice**:  
Use this option with caution. Set it to `true` only when you need a clean slate, such as after significant changes to your data model or during data migration. For routine updates, keep it `false` to preserve the existing index.

### 2. `batchSize`
**Description**:  
Defines the maximum number of events sent in a single batch during reindexing. The default value is `100`.  

**Best Practice**:  
Adjust the batch size based on system capabilities and event size. A larger batch size improves throughput but may increase memory usage and processing time. Monitor performance and fine-tune accordingly.

### 3. `payLoadSize`
**Description**:  
Specifies the maximum payload size (in bytes) for events sent in a batch. Default: `104,857,600 bytes` (100 MB).  

**Best Practice**:  
Ensure the payload size is within your system’s handling capacity. If memory issues or timeouts occur, reduce this value to improve stability.

### 4. `producerThreads`
**Description**:  
Indicates the number of threads used for producing events during reindexing. Default: `10`.  

**Best Practice**:  
Balance the number of threads with system CPU and I/O capacity. Increasing this number can improve throughput but may lead to contention if set too high.

### 5. `maxConcurrentRequests`
**Description**:  
Specifies the maximum number of concurrent requests sent to the search index at any given time. Default: `100`.  

**Best Practice**:  
Tune this value based on the indexing server’s capacity. Too many concurrent requests can overwhelm the server, leading to failures or slowdowns.

### 6. `maxRetries`
**Description**:  
Specifies the maximum number of retry attempts for failed requests. Default: `3 retries`.  

**Best Practice**:  
Keep this value reasonable to avoid excessive load during failures. Analyze failure patterns to optimize this setting.

### 7. `initialBackoff`
**Description**:  
Defines the initial backoff time (in milliseconds) before retrying a failed request. Default: `1000 ms` (1 second).  

**Best Practice**:  
Start with the default value. Increase it if failures occur frequently due to server overload or network issues.

### 8. `maxBackoff`
**Description**:  
Specifies the maximum backoff time (in milliseconds) for retries. Default: `10,000 ms` (10 seconds).  

**Best Practice**:  
Set this value to align with your application’s latency tolerance. A longer backoff can reduce system load during peak times but may slow recovery from errors.

### 9. `queueSize`
**Description**:  
Defines the internal queue size used for reindexing operations. Default: `100`.  

**Best Practice**:  
Adjust the queue size based on expected load and available memory resources. A larger queue can handle spikes in processing but requires more memory.

## Example Configuration for Best Practices

For high-performance systems, consider the following values as a starting point:

```json
{
  "batchSize": 300,
  "queueSize": 500,
  "producerThreads": 20,
  "maxConcurrentRequests": 500
}
```

Monitor system performance and adjust these parameters to optimize throughput and resource usage.


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