best database for large data

top 10000 GID, fariqi, reader, title from tgongwen order by fariqi DESC Time: 156 milliseconds. Scan count 1, logical read 289, physical read 0, pre-read 0. From the above, we can see that the speed of not sorting and the number of logical reads are equivalent to the speed of "order by clustered index columns, however, these queries are much faster than those of "order by non-clustered index columns. At the same time, when sorting by a field, whether in positive or reverse order, the speed is b

Original: Perform DBCC operations on very large SQL Server databases For database maintenance, mainly using DBCC CHECKDB, the following is the use of large databases, small databases are generally used directly: 1, 2008 (2005 I do not confirm) has implemented a snapshot check, that is, when you execute DBCC, The DBMS snapshots a

step is composed of Itemreader, Itemprocessor, Itemwriter, of course, according to different business needs, itemprocessor can do appropriate streamlining. At the same time, the framework provides a large number of Itemreader, Itemwriter implementations, providing support for a variety of data types such as Flatfile, XML, Json, DataBase, message, and so on. The

the following 3 aspects: Built for large data: Through the polybase of this data processing breakthrough technology Unified query structured, semi-structured and unstructured data, to help users use the most familiar standard SQL language can easily implement the Hadoop table and relational

The recent project involves a large amount of data. The specific problem is: monitoring digital TV signals, monitoring the transmitted code streams, and monitoring 20000 streams per second, each stream corresponds to more than 20 metrics, which are stored once per second. The data needs to be stored for 24 hours. This problem has been studied for several days: I.

Our demand for this example is to write a script that runs at 0 o ' Day. This script extracts data from a database that is updated in real time. Run an Excel table every day, showing the difference between 0 points of the day and yesterday 0 o'clock. In fact, a very simple demand, the key problem encountered is the amount of data. The amount of

the understanding of database lock, it is possible to use transaction isolation level in accordance with the specific business situation and to reduce the concurrency wait by manually specifying the locking method such as reducing the granularity of the lock. Optimistic Lock: Use the program to handle concurrency. Principles are relatively good understanding, the basic one can understand. There are about 3 ways of doing this Adds a ver

one table, the actual data to retain only more than 8w, so use Select INTO statement, saving data to a temporary table due to insufficient disk space Shrinking a Database Execute the SELECT INTO statement Execution of TRUNCATE TABLE, the size of the database file has not changed Shrinking a

Whether in daily business data processing or database import/export, a large amount of data may be inserted. The insertion method and the database engine will affect the insertion speed. This article aims to analyze and compare various methods theoretically and practically,

Large amount of data backup and restore, is always a difficult point. When MySQL is super 10G, it is slower to export with mysqldump. Recommend Xtrabackup here, this tool is much faster than mysqldump. First, Xtrabackup Introduction 1. What is Xtrabackup Xtrabackup is a tool for data backup of InnoDB, which supports online hot backup (without affecting

. The interval is crucial when detecting emerging trends-in the past five minutes, a particular project was purchased 100 times, obviously, this is more indicative of emerging trends than continuous purchases over the past five months. Traditional systems such as SSAs and SSRs require developers to track data in rows in a single dimension of A Multidimensional Dataset or timestamp column in transactional storage. Theoretically, tools used to identify

Large data is not only a popular topic, but also a real demand in the enterprise. Many companies are starting to work on large data analysis projects, but before that, we need a good deployment plan to ensure that the end result can be business services. Choosing the right technology is the first part of the plan, and