What does SOLR optimize do?
Optimize: This is similar to a defrag command on a hard drive. It will reorganize the index into segments (increasing search speed) and remove any deleted (replaced) documents.
How long does SOLR optimize take?
30-45min
This will take time depends on your solr data. For instance, 50G indexed data spikes nearly 90G and downs to optimized 25G data. And normally it will take 30-45min for this amount of data.
How can I improve my SOLR performance?
xml settings and avoid the most-common Solr search performance issues with Sitecore.
- Set the autoSoftCommit feature to 2 minutes.
- Set the autoCommit feature to 5 minutes.
- Use autowarmCount = 0 for All Cache Settings.
- Set maxRamMB to 200.
- Use the Default Values of True for Lazy Fields and Sorted Query.
What is a SOLR shard?
Solr sharding involves splitting a single Solr index into multiple parts, which may be on different machines. When the data is too large for one node, you can break it up and store it in sections by creating one or more shards, each containing a unique slice of the index.
What is indexing in Solr?
Indexing enables users to locate information in a document. Indexing collects, parses, and stores documents. Indexing is done to increase the speed and performance of a search query while finding a required document.
What is segment in SOLR?
The segment files in Solr are parts of the underlying Lucene index. You can read about the index format in the Lucene index docs. In principle, each segment contains a part of the index. New files get created when you add documents and you can completely ignore them.
What is the difference between Solr and Lucene?
Talking about Solr and Lucene, both are Apache projects that have been made to work together. However, Apache Solr is considered to be a standalone server and is a bit advanced. Whereas, Apache Lucene is a Java library-based solution used to index (store) and search data.
Is Solr a memory?
There are two types of memory Solr can use, heap memory and direct memory ( often called off-heap memory). Direct memory is used to cache blocks read from file system, similar to Linux file system cache. For heap memory, the following diagram shows various major consumers inside Solr.
How much RAM does Solr need?
If your OS, Solr’s Java heap, and all other running programs require 4GB of memory, then an ideal memory size for that server is at least 12GB. You might be able to make it work with 8GB total memory (leaving 4GB for disk cache), but that also might NOT be enough.
Is Solr scalable?
Lucene and Solr are both highly scalable search solutions. Depending on a multitude of factors, a single machine can easily host a Lucene/Solr index of 5 – 80+ million documents, while a distributed solution can provide subsecond search response times across billions of documents.
How does Solr index data?
By adding content to an index, we make it searchable by Solr. A Solr index can accept data from many different sources, including XML files, comma-separated value (CSV) files, data extracted from tables in a database, and files in common file formats such as Microsoft Word or PDF.
Are there any cases when Solr is slow?
There are some cases when commits could be slow when you have billions of records, Solr provides you more control over when data is committed using different options to control the commits timing, you will have to choose the option based on your application.
How to update the Lucene index in Solr?
You can simply commit the data to the index by sending commit=true parameter with update request, it will do the hard commit to all the Lucene index files to stable storage, it will ensure that all index segments should be updated and it could be costly when you have large data.
When do I need to disable autocommit in Solr?
There are also some cases where you can disable autoCommit altogether, for example, if you are migrating millions of records from a different datasource to Solr, you don’t want to commit the data upon every insert or even in case of bulk you don’t need it for every 2, 4 or 6 thousands insertions as still it will slow down migration.
What is the use of copyfield in Solr?
Solr provides very nice feature called copyField, it is a mechanism to store copy of multiple fields to a single field. The usage of copyField depends upon scenarios but the most common one is to create a single “search” field that will serve as the default query field when users or clients do not specify a field to query.
