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Update document is another important operation as part of indexing process. After running this program, you can see the list of index files created in that folder.

This operation is used when already indexed contents are updated and indexes become invalid. We update Document(s) containing Field(s) to Index Writer where Index Writer is used to update indexes. Once you are done with the creation of the source, the raw data, the data directory and the index directory, you can proceed with the compiling and running of your program. Java file tab active and use either the Run option available in the Eclipse IDE or use Ctrl F11 to compile and run your Lucene Tester application.

At times, it is helpful to think of the Lucene index as a database having a single table and the Documents as rows.

It is a good analogy when you frame it in terms of searching. However, there are many differences between a Lucene index and a database.

Lucene’s update Document operation is basically delete and insert wrapped into a single function.

All documents matching the Term parameter are deleted from the Lucene index and the supplied Document instance is then inserted into the index.

While Lucene allows multiple copies of the same document to exist in the index, the behavior of the update operation does not insert a copy of the supplied document for every match.

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This of course would require you to be able to identify the documents that need to be updated.

Follow these steps to create an Index Writer − Step 1 − Index Writer class acts as a core component which creates/updates indexes during the indexing process. Step 3 − Create a Lucene directory which should point to location where indexes are to be stored. IOException; import org.apache.lucene.analysis.standard. Standard Analyzer; import org.apache.lucene.document.

Step 4 − Initialize the Index Writer object created with the index directory, a standard analyzer having version information and other required/optional parameters.

One option is to throw away the entire index and then recreate it from the sources. For example you may have a lot of changes in your data and a high latency for updating the index is acceptable. Optimize(); // Should be done with low load only ...

In that case it might be the cheapest to do a full re-index each time. when less than 10% have changed updating can be more time efficient.