Sql Join Distinct

With the proliferation of data volume, Mysql+memcache has not met the needs of large-scale Internet applications, many organizations have chosen Redis as its architectural complement, however, redis the use of the threshold is not low, such as not supporting SQL, here for everyone to share the Redis use of the full raiders. Redis, one of the most closely watched NoSQL databases, has been used by many well-known internet companies, such as Sina Weibo, Pinterest and Viacom. However, being born with no support for SQL makes him look difficult ...

Method 1 delete yourtable where [id] not in (select max ([id]) from yourtable group by (name + value) b on a.id = b.id where b.id ...

SQL Union filters duplicate record statements and obtains data that is not duplicated $sql = "Union all->union----------------------How do I get the data from the following sentences? SELECT DISTINCT top PERCENT KIRINLDS.DBO.TBL personnel adjustment. Department name as department name from KIRINLDS.DBO.TBL person INNER JOIN ...

Hive in the official document of the query language has a very detailed description, please refer to: http://wiki.apache.org/hadoop/Hive/LanguageManual, most of the content of this article is translated from this page, Some of the things that need to be noted during the use process are added. Create tablecreate [EXTERNAL] TABLE [IF not EXISTS] table_name [col_name data_t ...

Using hive, you can write complex MapReduce query logic efficiently and quickly. In some cases, however, the Hive Computing task can become very inefficient or even impossible to get results, because it is unfamiliar with data attributes or if the Hive optimization convention is not followed. A "good" hive program still needs to have a deep understanding of the hive operating mechanism. Some of the most familiar optimization conventions include the need to write large tables on the right side of the join, and try to use UDF instead of transfrom ... Like。 Here are 5 performance and logic ...

Hive is the most widely used SQL on Hadoop tool, and recently many major data companies have introduced new SQL tools such as Impala,tez,spark, based on column or memory hot data, although many people have a view of hive, inefficient, slow query, and many bugs. But Hive is still the most widely used and ubiquitous SQL on Hadoop tool. Taobao survey analysis of the previous report, Taobao 90% of the business run in hive above. The ratio of the storm audio and video ...

Orient DB is a scalable document database that supports ACID transaction processing. Implemented using Java 5. Orientdb is an Open-source NoSQL database management system, written in Java, a document-type database that supports acid tx,http://www.aliyun.com/zixun/aggregation/16666.html "> Indexes,asynch queries,sql Layer ...

&http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp; This article is my understanding and thoughts on the level of the operators of distributed computing. Because the recent development of their own task is related to this aspect, the company has a self-study of the class flow calculation framework needs to do a layer of operator. My main analysis is the flow of the implementation of the operator on the system, compared with the existing computing framework and the industry is carrying out the project, analysis points ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Dougcutting based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapreduc ...