mongodb insert performance tuning

buffer pool, but will eventually need to write these pages to disk. Some general I/O tuning steps can speed up this process when I/O to a page is written to disk, such as: Distribute tablespaces across multiple containers (these containers map to different disks). Use the fastest hardware and storage management configuration possible, which includes factors such as disk and channel speed, write caching, and parallel write. Avoid RAID5 (unless used wi

take a look at the final test results? Note: The tested storage server is e5620 @ 2.40 GHz, with 24 GB memory and centos operating system. The suppression machine is e5504 @ 2.0 GHz, with 4 GB memory and Windows Server 2003 operating system, two Gigabit NICs are directly connected. From this test, we can see that the single process method is as follows: 1) MongoDB's non-secure insertion method has a very high performance at the beginning, bu

e5620 @ 2.40 GHz, with 24 GB memory and centos operating system. The suppression machine is e5504 @ 2.0 GHz, with 4 GB memory and Windows Server 2003 operating system, two Gigabit NICs are directly connected. From this test, we can see that the single process method is as follows: 1) MongoDB's non-secure insertion method has a very high performance at the beginning, but the performance decreases sha

) GTID2) in MySQL 5.6 gtid mode synchronous replication error cannot skip the workaround3) Improvement of Gtid replication in MySQL5.74) Gtid Replication traps5) Improvements to Gtid replication in MariaDB 10.1MySQL 5.6/5.7 Security recovery from library crashMariaDB 10.0/10.1 security recovery from vault crashSlave multi-threaded replication from librariesSlave supports multi-source replicationMySQL 5.7 Set synchronous replication filtering without restarting the MySQL service processThis artic

The performance test of MONGODB billion data volume was carried out, and the following items were tested:(All inserts are single-threaded and all reads are multithreaded)1) Normal insertion performance (the inserted data is about 1KB per piece)2) Bulk Insert performance (usi

memory and CentOs operating system. The suppression machine is E5504 @ 2.0 GHz, with 4 GB memory and Windows Server 2003 operating system, two Gigabit NICs are directly connected. From this test, we can see that the single process method is as follows: 1) Mongodb's non-secure insertion method has a very high performance at the beginning, but the performance decreases sharply after it reaches 20 million da

more than 3 million is a little more time-consuming.While the test is open to read data at the same time in a test phase, which reads the data simultaneously and writes the data, it is not found that this results in a sharp decrease in performance and a slight slowdown.Iv. Related SolutionsLater, asynchronously, I used a thread pool to synchronously perform all the insertions and reads, and found that it was significantly more efficient and did not d

handlersocket. Therefore, we can see that the number of QPS is significantly greater than the number of TPS, and batch insert operations significantly improve the overall performance. MongoDB adopts the method of merging operations internally. Data is first stored in the memory and then flushed to the disk. Therefore, from the test data, we can see that the

1. Test ToolsThis test chooses YCSB (Yahoo! Cloud System Benchmark) as the test Client tool. YCSB is a NoSQL test tool for Yahoo Open source, used to test the performance of a variety of NoSQL, project address: Https://github.com/brianfrankcooper/YCSB. The project's MongoDB directory has detailed installation and testing methods. YCSB supports common NoSQL database reads and writes, such as inserting, modif

We are going to perform a simple test on reading and writing MongoDB, Redis, and Tokyo Tyrant. To perform a fair test, we need to understand the implementation mechanism behind them. Below are some comparisons:Comparison of storage implementation:* Memory File Image (Memory-File Mapping) Redis, MongoDB* File + Cache Tokyo Tyrant* Memory: Redis, Tokyo TyrantKey/Value index format:* B + Tree:

you can't do it. MongoDB leads the nosql movement. Note that the most important thing we oppose is the SQL methodology. You can only get disappointed when using mangodb using SQL. Think about MongoDB's design philosophy: docization. _ Id is the file name, And MongoDB is a file system. Full-text search? Don't bother. Use a file name to find a file. A file name corresponds to a file, and you will never be di

MONGDB Performance pressure test, random query, data volume 100 million records Operating system centos6.4x64 bit From the test results, when MongoDB all the data into memory, query speed according to the size of the document, performance bottlenecks are usually in the network traffic and CPU processing performance (

. (11) In addition to prefix-style queries, regular expression queries cannot use indexes and execute longer than most selectors, and they should be used sparingly. (12) In an aggregation operation, $match the number of documents to be processed by the $ group operator in front of the $ group, by $match predecessor. (13) Modifying a document by using an operator typically provides better performance because it does not require a round-trip se

: Perform as root: It then monitors all packet requests to local localhost listening to MongoDB on the default 27017 port. 2.Mongostat This tool allows you to quickly view statistics field descriptions for a group of MongoDB instances in run:Insert: Insert amount per secondquery: Query amount per secondUpdate: Update amount per secondDelete: R

Tags: wan theory large number of connections coded pad memory alt modeThe performance test of MONGODB billion data volume was carried out, and the following items were tested:(All inserts are single-threaded and all reads are multithreaded) 1) Normal insertion performance (the inserted data is about 1KB per piece) 2) Bulk Ins