Sql Join And Where Clause

We want to do not only write SQL, but also to do a good performance of the SQL, the following for the author to learn, extract, and summarized part of the information to share with you! (1) Select the most efficient table name order (valid only in the Rule-based optimizer): The ORACLE parser processes the table names in the FROM clause in Right-to-left order, and the last table in the FROM clause (the underlying table driving tables) is processed first, In the case where multiple tables are included in the FROM clause, you must select the table with the least number of records as the underlying table. If...

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 ...

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 ...

1, use the index to traverse the table faster. The index created by default is a non-clustered index, but sometimes it is not optimal. Under non-clustered indexes, the data is physically stored on the data page. Reasonable index design should be based on the analysis and prediction of various inquiries. In general: a. There are a large number of duplicate values, and often range query (>, <,> =, <=) and order by, group by occurred columns, consider the establishment of cluster index; Column, and each column contains duplicate values ​​can be ...

1, use the index to traverse the table faster. The index created by default is a non-clustered index, but sometimes it is not optimal. Under non-clustered indexes, the data is physically stored on the data page. Reasonable index design should be based on the analysis and prediction of various inquiries. In general: a. A large number of duplicate values, and often range query (>, <,> =, <=) and order by, group by occurred column, consider the establishment of cluster index; b. Column, ...

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 ...

In our development of the efficiency has been a problem, especially for a lot of large data operations, today we ran into a random query data, at first we may think of the simplest order by RAND () to operate but the efficiency is not flattering ah. Recently, because of the need to study the MySQL random extraction implementation method. For example, to randomly extract a record from the TableName table, the general wording is: SELECT * from TableName ORDER by RAND () LIM ...