Solr jvm memory monitor1/5/2024 ![]() Let's now look at how we can monitor all those metrics that are crucial to our indexing and searching. Each search phase requires I/O to read the data from disk, memory to store the results and intermediate steps required to perform the search, CPU cycles to calculate everything and network to transport the data. The gather phase is dedicated to rendering the search results by retrieving the needed documents from the shards that have them indexed. The scatter phase is dedicated to finding which shards have the matching documents, the identifier of those documents and their score. Each distributed search is done in two phases - scatter and gather. When you send a search query to SolrCloud cluster, the node that is hit by the query initially propagates the data to shards that are needed to be queried in order to provide full data visibility. This can cause additional I/O requirements - as the data indexing may also cause segment merging and finally it needs to be refreshed in order to be visible for searching, which requires yet another I/O operation. ![]() The data is then indexed and written onto the disk into the inverted index format. The leader stores the data in the write-ahead log called transaction log and, depending on the replica type, send the data to the replica for processing. When the data is pushed to any of the Solr nodes that are part of the cluster, the first thing that is done is forwarding the data to a leader shard. However, for that to happen we need an additional piece of software - Apache Zookeeper cluster to help Solr manage and configure its nodes. Physical copies of the data, placed in so-called shards can be created on demand in the form of physical replicas and replicated between them in a near real-time manner allowing for true fault tolerance and high availability. It is based on the assumption that the data is distributed among a virtually unlimited number of nodes and each node can perform indexing and search processing roles. Because of that, the second type of architecture was introduced with Solr 4.0 release - the SolrCloud. Having a single master node is not something that we would call fault tolerant, because of having a single point of failure. We already see a dozen of places that we should monitor and have knowledge about. Each node does that on its own and works separately copying the changed data over the network. The slave servers use an HTTP protocol to copy the binary data from the master node. Once the data has been written in the form of segments on the master’s disk, it can be replicated to the slave servers. The segments can also be combined together into larger segments in a process called segment merging for performance reasons - the more segments you have, the slower your searches can be and vice versa. The disk-based inverted index is divided into smaller, immutable pieces called segments, which are then used for searching. ![]() When the data is pushed to the master it is transformed into a so-called inverted index based on the configuration that we provide. The legacy architecture also called master-slave - it is based on a clear distinction between the master server which is responsible for indexing the data and the slave servers responsible for delivering the search and analysis results. Such a critical part of the whole architecture is needed to be both fault tolerant and highly available. It is used as a search and analysis engine for your data - part of it or all. When running Solr it is usually a crucial part of the system. When dealing with SolrCloud clusters you not only want to monitor per node metrics but also cluster-wide information and the metrics related to Zookeeper. When first thinking about installing Solr you usually ask yourself a question - should I go with the master-slave environment or should I dedicate myself to SolrCloud? This question will remain unanswered in this blog post, but what we want to mention is that it is important to know which architecture you will monitor. The second part of the series covers Solr open source monitoring tools and identify the tools and techniques you need to help you monitor and administer Solr and SolrCloud in production. ![]() What is the correct way to choose the heap threshold to give to solr?Īt the moment, among the different cores, the only one that exceeds a few hundred megabytes is sitecore_analytics_index which has a size of 32.As the first part of the three-part series on monitoring Apache Solr, this article explores which Solr metrics are important to monitor and why. Solr Exception: Error opening new searcher Caused by: .Alread圜losedException: this IndexWriter is closed Caused by: : Java heap space Recently we have had some issues like this: In our sitecore 8.2 installation we use Solr 5.1.0 as an indexing system.
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