mongodb query performance

Mongodb query, mongodb1. query a single record > db.choice.findOne() 2. Specify query conditions during Query > db.choice.find({"_id":"005a38d5"}) All queries by default {} Return Column > db.choice.find({"_id":"005a38d5"},{"title":1,"results":1}){ "_id" : "005a38d5", "

are settings, there are two ways to set the method and level, one is to add the –slowms boot parameter configuration. The second is to add the second parameter when calling Db.setprofilinglevel: Db.setprofilinglevel (level, slowms) db.setprofilinglevel (1, 10);2. Query Profiling RecordsUnlike MySQL's slow query log, MongoDB profile records are directly present i

cursor.nocursortimeout () method: var mycursor = Db.users.find (). Nocursortimeout (); After setting the nocursortimeout option, you must either close the cursor manually with cursor.close () or by exhausting the cursor ' s results. See your driver documentation for information on setting the nocursortimeout option.Cursor IsolationAs a cursor returns documents, other operations could interleave with the query. For the MMAPV1 storage engine, interveni

This is a creation in Article, where the information may have evolved or changed. More Articles Quick Smart Programmer Community Front-end input query criteria, background based on query criteria, query MongoDB, filtered results are displayed again. Front page: Query condi

Label:Recent projects need to use MONGODB, so downloaded the source of MongoDB on the internet, according to the sample written test code, but found a very strange problem: the speed of inserting records faster than the speed of data acquisition, and the most important problem is that the speed of data acquisition is unacceptable.Test scenario: Main Document storage personnel basic information, sub-document

Mongodb entry-8 query 3 continue to learn about mongodb query $ or $ nor $ or, or the meaning is identified as long as there is a match. $ nor is opposite to $ or, as long as $ or can be found as the removed part. [html] db. user. find () {_ id: ObjectId (5198c286c686eb50e2c843b2), name: user0, age: 0} {_ id

capacity + High frequency access to data capacity, set by Storage.wiredTiger.engineConfig.cacheSizeGB or--WIREDTIGERCACHESIZEGB. View and evaluate by monitoring the db.serverstatus () command Write-heavy applications with Ssd:sata interface SSD provide strong sequential write performance, can improve the writing speed of MongoDB data and jounal log files, and the most powerful is the random read

of the queries is different from the order in which the indexes are established4. Combined IndexAs with other database products, MongoDB also has a combined index, Next I'll set up a composite index on addr.ctiy and addr.state, when creating a composite index, the 1 after the field indicates ascending, 1 means descending, 1 or 1 is related to the time of the sort or the query within the specified range.At

Tags: mongodb skip limit sortMongoDB uses cursors to process the set of result documents found by the Find query;Examples of use of cursors:>varcursor=db.post.find ({"Name.firstname": "Joe"}) >cursor { "_id" :objectid ("54ace1394ba07ed75df68f90"), "name" :{ " FirstName ":" Joe "," LastName ":" Schome "}," Age "NBSP;:NBSP;28NBSP;} { "_id" :objectid ("54ace753eab1d0ba4abb48ab"), "name" NBSP;: { "FirstName" :

Tags: mongodbIn the last blog, we talked about the basic operation of MongoDB, including insert, query, remove and update. Now on this blog, we'll further hava a good understanding of querying operation.At first, let's create the recors for testing. As the following picture depicts.Condition Expression1. 2. $allThis operation was analogous to the $in operation. But the difference is, $all operation requires

Query (table 300 million data): Simultaneous connection number op/s3 8K5 10K8 16K20K25K32K40K48K57KThe memory even index cannot be completely lowered: Cache:data = 1:10 Query (table 300 million data): Simultaneous connection number op/s3 3.4K5 4.5K8 9.3K11K14K20K24K25K34K(Click to view larger image)The index is all in memory:Cache:data is 4:10The index is not all in memoryCache:d

Lock% (or mongostat command line output) indicator in MongoDB's MMS Monitor. In general, if DB Lock is more than 70-80% and continues to be considered saturated. How to solve this problem? Scenario One: sharding This is MongoDB's standard answer if you have enough hardware resources. Sharding is the ultimate way to solve most of the performance bottleneck problems. Scenario Two: Sub-Library This is a very effective alternative. The practice is to sep

default setting, there are two kinds of setting method and level, one is by adding –slowms boot parameter configuration. The second is to invoke Db.setprofilinglevel with the second argument: Db.setprofilinglevel (level, slowms) db.setprofilinglevel (1, 10); 2. Query Profiling Records Unlike MySQL's slow query log, the MongoDB profile record is dir

This example for you to share the Java Operation MongoDB Fuzzy query and paging query for your reference, the specific contents are as follows Fuzzy query conditions:1. Perfect MatchPattern pattern = pattern.compile ("^name$", pattern.case_insensitive);2, right matchingPattern pattern = pattern.compile ("^.*name$", pa

performance and business to set), so set a big meaningless. If you set a reasonable value, you reach this value and MongoDB the new connection request to avoid being dragged down by too many connections.2.indexcounters:btree:misses index of the number of misses, and the ratio of hits to consider whether the index is correctly established. You see my "missratio": 3.543930204420982e-7, very healthy bar. So t

convert each document from BSON to a JavaScript Object and run it through the $ where expression. This process cannot use indexes, so the query speed is much slower than the regular query speed. If necessary, you can use the regular query as the pre-filter. If you can use the index, you can use the index to filter according to the non-$ where clause, and then us