Generally, it all boils down to performance. Multi-queries, or query batches, let you send multiple search queries to Manticore in one go (more formally, one network request). That is, distributed tables are fully transparent to the application, and actually there’s no way to tell whether the table you queried was distributed or local. merges all the results together, removing the duplicatesįrom the application’s point of view, there are no differences between searching through a regular table, or a distributed table at all.retrieves remote agent’s search results.at the same time searches configured local tables (while the remote agents are searching).When Manticore receives a query against distributed table, it does the following: This kind of table only contains references to other local and remote tables - so it could not be directly reindexed, and you should reindex those tables which it references instead. and route your queries to the distributedtable.configure a special distributed table on some of the searchd instances.put different parts of your dataset to different instances.setup several instances of Manticore on different servers.The key idea is to horizontally partition searched data across search nodes and then process it in parallel. billions of records and terabytes of text). This is essential for applications which need to search through huge amounts data (ie. max queries/sec) in multi-server, multi-CPU or multi-core environments. Distributed searching is useful to improve query latency (i.e. To scale well, Manticore has distributed searching capabilities.
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