Sql Describe All Tables

The Big data field of the 2014, Apache Spark (hereinafter referred to as Spark) is undoubtedly the most attention. Spark, from the hand of the family of Berkeley Amplab, at present by the commercial company Databricks escort. Spark has become one of ASF's most active projects since March 2014, and has received extensive support in the industry-the spark 1.2 release in December 2014 contains more than 1000 contributor contributions from 172-bit TLP ...

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 ...

Copyright Notice: Original works, allow reprint, reprint, please be sure to hyperlink form to indicate the original source of the article, author information and this statement. Otherwise, legal liability will be held. http://knightswarrior.blog.51cto.com/1792698/388907. First of all, the Templars are delighted to receive the attention and support of the cloud Computing series, which has been in preparation for several months, and finally released the first one today (because the article is too long, it is two pieces, and this is an article). In these months through constant making ...

As we all know, the big data wave is gradually sweeping all corners of the globe. And Hadoop is the source of the Storm's power. There's been a lot of talk about Hadoop, and the interest in using Hadoop to handle large datasets seems to be growing. Today, Microsoft has put Hadoop at the heart of its big data strategy. The reason for Microsoft's move is to fancy the potential of Hadoop, which has become the standard for distributed data processing in large data areas. By integrating Hadoop technology, Microso ...

After more than eight years of practice, from Taobao's collection business to today to support all of Alipay's core business, and in the annual "Double Eleven Singles Day" continue to create a world record for the transaction database peak processing capacity.

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

This article focuses on how Eleme big data team reduced the user access threshold by unifying the entry of the computing engine. How to enable users to self-analyze task anomalies and failure causes, and how to monitor cluster computing/storage resource consumption, monitor cluster status, and monitor abnormal tasks from the task data itself generated by the cluster.

Hadoop is often identified as the only solution that can help you solve all problems. When people refer to "Big data" or "data analysis" and other related issues, they will hear an blurted answer: hadoop! Hadoop is actually designed and built to solve a range of specific problems. Hadoop is at best a bad choice for some problems. For other issues, choosing Hadoop could even be a mistake. For data conversion operations, or a broader sense of decimation-conversion-loading operations, E ...

Apache Pig, a high-level query language for large-scale data processing, works with Hadoop to achieve a multiplier effect when processing large amounts of data, up to N times less than it is to write large-scale data processing programs in languages ​​such as Java and C ++ The same effect of the code is also small N times. Apache Pig provides a higher level of abstraction for processing large datasets, implementing a set of shell scripts for the mapreduce algorithm (framework) that handle SQL-like data-processing scripting languages ​​in Pig ...