import org.codelibs.fess.entity.DataStoreParams;
import org.codelibs.fess.util.ComponentUtil;

/**
 * Abstract base class for document ingesters that process and transform documents
 * before they are indexed. Ingesters can be used to modify document content,
 * extract additional metadata, or perform other transformations during the
 * indexing process.
 *

        return u * v / a;
    }

    /**
     * Calculates a MAC (Message Authentication Code) for PAC data validation.
     * @param type the checksum type to use
     * @param keys map of available Kerberos keys indexed by encryption type
     * @param data the data to calculate the MAC for
     * @return the calculated mac bytes
     * @throws PACDecodingException if the MAC calculation fails or required keys are missing
     */

     */
    @Size(max = 10)
    public String suggestSearchLog;

    /**
     * Enable or disable search suggestions based on document content.
     * When enabled, suggestions are generated from indexed documents.
     */
    @Size(max = 10)
    public String suggestDocuments;

    /**
     * Number of days to keep suggestion search logs before purging.

## Pre-Migration Planning

### 1. Assessment Phase

Before starting migration, assess your current system:

- **Document Count**: Total number of indexed documents
- **Index Size**: Storage requirements for search indices
- **Crawl Sources**: URLs, file shares, databases being indexed
- **Custom Configurations**: URL patterns, security rules, metadata fields
- **Search Features**: Facets, suggestions, security filtering, ranking rules

    /** Logger instance for this factory class. */
    private static final Logger logger = LogManager.getLogger(DataStoreFactory.class);

    /**
     * Map containing registered data store instances indexed by their names and class simple names.
     * All keys are stored in lowercase for case-insensitive lookup.
     */
    protected Map<String, DataStore> dataStoreMap = new LinkedHashMap<>();

    /**

            logger.info("Parsing words from indexed documents.");
            suggestHelper.indexFromDocuments(ret -> {
                logger.info("Success indexing from documents.");
                latch.countDown();
            }, t -> {
                logger.error("Failed to update suggest index.", t);
                exitCode.set(1);
                latch.countDown();
            });

 * This class manages the process of updating the search index with documents from
 * data stores, including bulk operations, document transformation, and error handling.
 */
public class IndexUpdateCallbackImpl implements IndexUpdateCallback {
    private static final Logger logger = LogManager.getLogger(IndexUpdateCallbackImpl.class);

    /**
     * Default constructor for index update callback implementation.

    });
```

## Advanced Usage

### Index from Existing Documents

```java
import org.codelibs.fess.suggest.index.contents.document.ESSourceReader;

// Index suggestions from existing Elasticsearch documents
DocumentReader reader = new ESSourceReader(
    client,
    suggester.settings(),
    "content-index",        // source index
    "document"             // document type
);

    /**
     * Constructs KerberosEncData from encrypted token bytes.
     *
     * @param token the encrypted Kerberos token
     * @param keys map of encryption keys indexed by key type
     * @throws PACDecodingException if decoding fails
     */
    public KerberosEncData(byte[] token, Map<Integer, KerberosKey> keys) throws PACDecodingException {

 */
public class ProcessHelper {
    /** Logger instance for this class */
    private static final Logger logger = LogManager.getLogger(ProcessHelper.class);

    /** Map of running processes indexed by session ID */
    protected final ConcurrentHashMap<String, JobProcess> runningProcessMap = new ConcurrentHashMap<>();

    /** Timeout in seconds for process destruction */
    protected int processDestroyTimeout = 10;