Non-relational databases are attracting more attention day by day. The main limitation is that today's complicated data are indeed connected. Isn't it convenient to connect databases as we connect tables in RDBMS? Of course, I just mean simple cases. Imagine three tables of Articles, Tags, Relationships. In a RDBMS like Mysql, we can run three queries to
非关系型数据库日益受到更多关注。主要限制是今天复杂的数据确实是连通的。在我们连接RDBMS中的表时连接数据库不方便吗?当然,我只是简单的案例。想象一下三篇文章,标签,关系。在像Mysql这样的RDBMS中,我们可以运行三个查询
1. Find ID of a given tag
2. Find Articles connected with the captured Tag ID
3. Fetch the contents of Articles tagged with the term
Instead of three queries, we perform a single query by JOIN. I think three queries in a key/value database like BerkeleyDB is faster than a JOIN query in Mysql.
我们通过JOIN执行单个查询,而不是三个查询。我认为像BerkeleyDB这样的键/值数据库中的三个查询比Mysql中的JOIN查询要快。
Is this idea practical? Or other issues are involved to ignore this approach?
这个想法是否实用?或者其他问题涉及忽略这种方法?
3 个解决方案
#1
2
NoSQL databases can support relational data models just fine. You're just left to implement the relational mapping yourself in your application, and that effort is typically not insignificant.
NoSQL数据库可以很好地支持关系数据模型。您只需在应用程序中自己实现关系映射,这种努力通常并非无关紧要。
In some applications this extra effort will be worthwhile. Perhaps you only have a small number of tables and the joins you need are very simple. Or perhaps you've done some performance evaluation between a traditional relational DBMS and a NoSQL alternative and found that the NoSQL option is more appropriate for your needs for any number of reasons (performance, scalability, flexibility, whatever).
在某些应用中,这种额外的努力是值得的。也许你只有少量的表,你需要的连接非常简单。或者您可能已经在传统的关系型DBMS和NoSQL替代方案之间进行了一些性能评估,并发现NoSQL选项更适合您的需求,原因有多种(性能,可伸缩性,灵活性等等)。
You should keep one thing in mind, however. A typical SQL DBMS is basically a NoSQL DB with an optimized, well-built relational engine in front of it. Some databases even let you bypass the relational layer and treat their system like a pure NoSQL DB.
但是,你应该记住一件事。典型的SQL DBMS基本上是一个NoSQL DB,它前面有一个优化的,精心构建的关系引擎。有些数据库甚至允许您绕过关系层并将其系统视为纯粹的NoSQL DB。
Therefore, the moment you start to build your own relational mappings and joins on top of a NoSQL DB you should ask yourself, "Didn't someone build this for me already?" The answer may well be "yes", and the solution might be to go with a traditional SQL DBMS.
因此,当你开始构建自己的关系映射并加入NoSQL数据库时,你应该问自己:“有没有人为我建立这个?”答案可能是“是”,解决方案可能是使用传统的SQL DBMS。
To answer the "3 query" part of your question specifically, the answer is "maybe". You certainly might be able to make such a query run faster in a NoSQL DB than in an RDBMS, but you need to keep in mind that there are more things to consider here than just the raw speed of your query:
要具体回答问题的“3查询”部分,答案是“也许”。您当然可以在NoSQL DB中比在RDBMS中更快地运行这样的查询,但是您需要记住,这里需要考虑的事情多于查询的原始速度:
- The technical debt you will incur as you build join-like functionality that you wouldn't have had to build otherwise
- The time it will take you to build, test and optimize your query code which will likely be more significant than writing a simple SQL query
- Any difference in transactional guarantees or other typical product features (replication, management tools, etc) which you may lose or gain depending on the NoSQL option you choose
- The ability to hire DBMs who know how to run your database from an operational perspective
当您构建类似连接的功能时,您将产生的技术债务,否则您将不必构建
您需要花时间构建,测试和优化查询代码,这可能比编写简单的SQL查询更重要
根据您选择的NoSQL选项,您可能会丢失或获得的事务保证或其他典型产品功能(复制,管理工具等)的任何差异
能够从操作角度聘请知道如何运行数据库的DBM
You might review that list and say to yourself, "No big deal, I'm running a simple app with only a few thousand DB entries and I'll maintain it myself". If so, knock yourself out - Berkeley (and other NoSQL options) would work fine. I've used Berkeley many times for those kinds of applications. But you may have a different answer if you are building the back-end for a significantly-sized SaaS product which might soon have millions of users and very complex queries.
您可以查看该列表并对自己说:“没什么大不了的,我正在运行一个只有几千个数据库条目的简单应用程序,我会自己维护它”。如果是这样,那就把自己搞得一团糟 - 伯克利(以及其他NoSQL选项)可以正常工作。我已经多次使用伯克利来进行这类应用。但是,如果要为大规模的SaaS产品构建后端,可能会有很多用户和非常复杂的查询,那么您可能会有不同的答案。
We can't give a one-size-fits-all answer, unfortunately. You'll have to make the judgement call yourself based on the needs of you application and organization.
不幸的是,我们无法给出一个通用的答案。您必须根据应用程序和组织的需要自行判断。
#2
1
Sure, a single record join is pretty speedy in either solution, but that's not the big advantage of joins. Joins are useful when you're joining many, many rows with many, many other rows. Imagine if, in your example, you wanted to do that for 100 different tags. Without joins, you're talking 300 queries to SQL's one.
当然,在任何一种解决方案中,单个记录连接都非常快速,但这并不是连接的最大优势。当您加入包含许多其他行的许多行时,联接非常有用。想象一下,在您的示例中,您是否想要为100个不同的标签执行此操作。没有连接,你就是在谈论SQL的300个查询。
#3
0
Another solution on noSql systems is playOrm. It does Joins BUT only in partitions so the table can be infinite size, but the partitions have to be on par with the size of RDBMS tables. It does all the fancy hibernate stuff as well for you with all the related annotations though it has some differences and will be adding Embedded for use when you denormalize. It makes things much easier. Typically dealing with nosql is kind of a pain in all the translation logic you have to do and all the manual indexing and updates and removes from the index....playOrm does all this for you instead.
noSql系统的另一个解决方案是playOrm。它只在分区中加入BUT,因此表可以是无限大小,但分区必须与RDBMS表的大小相同。虽然它有一些不同之处,但它会为你提供所有相关注释的所有花哨的hibernate内容,并且会在你反规范化时添加Embedded。它使事情变得更容易。通常处理nosql是你必须做的所有翻译逻辑中的一种痛苦,并且所有手动索引和更新都会从索引中删除.... playOrm会为你做所有这些。
#1
2
NoSQL databases can support relational data models just fine. You're just left to implement the relational mapping yourself in your application, and that effort is typically not insignificant.
NoSQL数据库可以很好地支持关系数据模型。您只需在应用程序中自己实现关系映射,这种努力通常并非无关紧要。
In some applications this extra effort will be worthwhile. Perhaps you only have a small number of tables and the joins you need are very simple. Or perhaps you've done some performance evaluation between a traditional relational DBMS and a NoSQL alternative and found that the NoSQL option is more appropriate for your needs for any number of reasons (performance, scalability, flexibility, whatever).
在某些应用中,这种额外的努力是值得的。也许你只有少量的表,你需要的连接非常简单。或者您可能已经在传统的关系型DBMS和NoSQL替代方案之间进行了一些性能评估,并发现NoSQL选项更适合您的需求,原因有多种(性能,可伸缩性,灵活性等等)。
You should keep one thing in mind, however. A typical SQL DBMS is basically a NoSQL DB with an optimized, well-built relational engine in front of it. Some databases even let you bypass the relational layer and treat their system like a pure NoSQL DB.
但是,你应该记住一件事。典型的SQL DBMS基本上是一个NoSQL DB,它前面有一个优化的,精心构建的关系引擎。有些数据库甚至允许您绕过关系层并将其系统视为纯粹的NoSQL DB。
Therefore, the moment you start to build your own relational mappings and joins on top of a NoSQL DB you should ask yourself, "Didn't someone build this for me already?" The answer may well be "yes", and the solution might be to go with a traditional SQL DBMS.
因此,当你开始构建自己的关系映射并加入NoSQL数据库时,你应该问自己:“有没有人为我建立这个?”答案可能是“是”,解决方案可能是使用传统的SQL DBMS。
To answer the "3 query" part of your question specifically, the answer is "maybe". You certainly might be able to make such a query run faster in a NoSQL DB than in an RDBMS, but you need to keep in mind that there are more things to consider here than just the raw speed of your query:
要具体回答问题的“3查询”部分,答案是“也许”。您当然可以在NoSQL DB中比在RDBMS中更快地运行这样的查询,但是您需要记住,这里需要考虑的事情多于查询的原始速度:
- The technical debt you will incur as you build join-like functionality that you wouldn't have had to build otherwise
- The time it will take you to build, test and optimize your query code which will likely be more significant than writing a simple SQL query
- Any difference in transactional guarantees or other typical product features (replication, management tools, etc) which you may lose or gain depending on the NoSQL option you choose
- The ability to hire DBMs who know how to run your database from an operational perspective
当您构建类似连接的功能时,您将产生的技术债务,否则您将不必构建
您需要花时间构建,测试和优化查询代码,这可能比编写简单的SQL查询更重要
根据您选择的NoSQL选项,您可能会丢失或获得的事务保证或其他典型产品功能(复制,管理工具等)的任何差异
能够从操作角度聘请知道如何运行数据库的DBM
You might review that list and say to yourself, "No big deal, I'm running a simple app with only a few thousand DB entries and I'll maintain it myself". If so, knock yourself out - Berkeley (and other NoSQL options) would work fine. I've used Berkeley many times for those kinds of applications. But you may have a different answer if you are building the back-end for a significantly-sized SaaS product which might soon have millions of users and very complex queries.
您可以查看该列表并对自己说:“没什么大不了的,我正在运行一个只有几千个数据库条目的简单应用程序,我会自己维护它”。如果是这样,那就把自己搞得一团糟 - 伯克利(以及其他NoSQL选项)可以正常工作。我已经多次使用伯克利来进行这类应用。但是,如果要为大规模的SaaS产品构建后端,可能会有很多用户和非常复杂的查询,那么您可能会有不同的答案。
We can't give a one-size-fits-all answer, unfortunately. You'll have to make the judgement call yourself based on the needs of you application and organization.
不幸的是,我们无法给出一个通用的答案。您必须根据应用程序和组织的需要自行判断。
#2
1
Sure, a single record join is pretty speedy in either solution, but that's not the big advantage of joins. Joins are useful when you're joining many, many rows with many, many other rows. Imagine if, in your example, you wanted to do that for 100 different tags. Without joins, you're talking 300 queries to SQL's one.
当然,在任何一种解决方案中,单个记录连接都非常快速,但这并不是连接的最大优势。当您加入包含许多其他行的许多行时,联接非常有用。想象一下,在您的示例中,您是否想要为100个不同的标签执行此操作。没有连接,你就是在谈论SQL的300个查询。
#3
0
Another solution on noSql systems is playOrm. It does Joins BUT only in partitions so the table can be infinite size, but the partitions have to be on par with the size of RDBMS tables. It does all the fancy hibernate stuff as well for you with all the related annotations though it has some differences and will be adding Embedded for use when you denormalize. It makes things much easier. Typically dealing with nosql is kind of a pain in all the translation logic you have to do and all the manual indexing and updates and removes from the index....playOrm does all this for you instead.
noSql系统的另一个解决方案是playOrm。它只在分区中加入BUT,因此表可以是无限大小,但分区必须与RDBMS表的大小相同。虽然它有一些不同之处,但它会为你提供所有相关注释的所有花哨的hibernate内容,并且会在你反规范化时添加Embedded。它使事情变得更容易。通常处理nosql是你必须做的所有翻译逻辑中的一种痛苦,并且所有手动索引和更新都会从索引中删除.... playOrm会为你做所有这些。