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SQL和SQL-MR查询在Teradata aster内部如何工作?

[英]How does SQL and SQL-MR query works internally in Teradata aster?

I'm currently exploring Tera data Aster(Aster express 6). 我目前正在探索Tera数据Aster(Aster Express 6)。 I've gone through documentation and blogs but no where it is explained how querying works. 我浏览了文档和博客,但没有解释查询的工作原理。 since it is distributed how they sql and sql-mr fetches data, do they generate map reduce jobs internally ? 由于它是分布式的,因此sql和sql-mr如何获取数据,它们是否在内部生成map reduce作业?

for example customer table has 10 records which are distributed by hash(customer id) and say they're 3 workers(nothing but nodes in asterdata), data split among them as 3 records each on two nodes and 4 on one node. 例如,客户表有10条记录,这些记录按哈希(客户ID)分布,并说他们是3位工作人员(除了asterdata中的节点),数据在其中被拆分为3条记录,每条记录分别位于两个节点上,而4条记录在一个节点上。

In SQL the simple select * from customers; 在SQL中,简单地从客户中选择*; will work in this case? 在这种情况下会工作吗?

but in aster data this query works. 但在aster数据中,此查询有效。

How does it fetches records from 3 nodes? 它如何从3个节点获取记录? if normal sql query can fecth records then why we need MapReduce, we can use mutliple sub queries to accomplish are tasks? 如果普通的sql查询可以感染记录,那么为什么我们需要MapReduce,我们可以使用mutliple子查询来完成任务呢?

If data is distributed among multiple machines then mapreduce is the only way to process data? 如果数据分布在多台计算机之间,那么mapreduce是处理数据的唯一方法吗?

It'll really help me if someone explains this! 如果有人解释这会对我有很大帮助!

Pradi Pradi

由Teradata赞助的白皮书(www.teradata.com/white-paper/Using-SQL-MapReduce-for-Advanced-Analytical-Queries/)解释了将MapReduce与SQL结合使用的理由,应该是改进的一个良好的起点。理解。

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