Using Subqueries In Sql

The greatest fascination with large data is the new business value that comes from technical analysis and excavation. SQL on Hadoop is a critical direction. CSDN Cloud specifically invited Liang to write this article, to the 7 of the latest technology to do in-depth elaboration. The article is longer, but I believe there must be a harvest. December 5, 2013-6th, "application-driven architecture and technology" as the theme of the seventh session of China Large Data technology conference (DA data Marvell Conference 2013,BDTC 2013) before the meeting, ...

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...

A few suggestions to improve SQL execution efficiency: Try not to include subqueries in where; queries about time, try not to write: where To_char (dif_date, ' yyyy ') =to_char (' 2007-07-01 ', ' yyyy '); In the filter condition, the condition in which the maximum number of records can be filtered must be placed at the end of the WHERE clause, and the last table (underlying table, driving table) in the FROM clause will be first ...

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 ...

As a software developer or DBA, one of the essential tasks is to deal with databases, such as MS SQL Server, MySQL, Oracle, PostgreSQL, MongoDB, and so on. As we all know, MySQL is currently the most widely used and the best free open source database, in addition, there are some you do not know or useless but excellent open source database, such as PostgreSQL, MongoDB, HBase, Cassandra, Couchba ...

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 ...

Before yarn, Hadoop was only available for offline processing scenarios. Based on real-time demand, organizations have developed their own streaming framework, this time we are talking about two sql-on-hadoop projects, as well as two well-known Hadoop solution Providers--impala vs. Stinger. Singer:stinger first appeared in Hive 0.11 (HDP 1.3), with a total of 3 phase goals, of which phase I and II had been delivered. Through the hortonwo ...

Facebook, a world-renowned social networking site, has more than 300 million active users, of which about 30 million users update their status at least once a day; users upload a total of more than 1 billion photos and 10 million videos a month; Week to share 1 billion content, including journals, links, news, Weibo and so on. Therefore, the amount of data that Facebook needs to store and process is huge. Everyday, 4TB of compressed data is added, 135TB of data is scanned, and more than 7,500 Hive tasks are performed on the cluster.

"Guide" the author (Xu Peng) to see Spark source of time is not long, note the original intention is just to not forget later. In the process of reading the source code is a very simple mode of thinking, is to strive to find a major thread through the overall situation. In my opinion, the clue in Spark is that if the data is processed in a distributed computing environment, it is efficient and reliable. After a certain understanding of the internal implementation of spark, of course, I hope to apply it to practical engineering practice, this time will face many new challenges, such as the selection of which as a data warehouse, HB ...

First, the importance of the index The index is used to quickly find a column in a particular value of the line. Instead of using an index, MySQL must start with the first record and then read the entire table until it finds the relevant row. The larger the table, the more time it takes. If the table in the query column index, MySQL can quickly reach a location to search the middle of the data file, there is no need to see all the data. Note that if you need to access most of the rows, sequential reads are much faster since we avoid disk searches. If you use Xinhua Dictionary to find "Zhang" the Chinese characters, do not use the directory, then ...