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Learn NodeJS in 1...
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Hadoop Explained
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by Aravind Shenoy (Goodreads Author)
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Rethinking the In...
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“In a RDBMS, since all the column names and types are defined at the table level, this information does not need to be replicated in each row. MongoDB, by contrast, doesn’t know, at the collection level, what fields are present in each document, nor does it know their types, so this information must be stored on a per-document basis.”
― Rick Copeland, MongoDB Applied Design Patterns

“The fewer documents in RAM, the more likely the server is to page fault to retrieve documents, and ultimately page faults lead to random disk I/O.”
― Rick Copeland, MongoDB Applied Design Patterns

“larger”
― Rick Copeland, MongoDB Applied Design Patterns

“The constraints of a toolset help to define patterns for solving problems. In the case of MongoDB, one of those constraints is the lack of atomic multidocument update operations. The patterns we use in MongoDB to mitigate the lack of atomic multidocument update operations include document embedding and complex updates for basic operations, with optimistic update with compensation available for when we really need a two-phase commit protocol. When designing your application to use MongoDB, more than in relational databases, you must keep in mind which updates you need to be atomic and design your schema appropriately.”
― Rick Copeland, MongoDB Applied Design Patterns

Viktor Mayer-Schönberger
“the “data scientist,” which combines the skills of the statistician, software programmer, infographics designer, and storyteller.”
― Viktor Mayer-Schönberger, Big Data: A Revolution That Will Transform How We Live, Work and Think

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