Download E-books MongoDB Cookbook - Second Edition PDF

By Amol Nayak

Harness the newest positive aspects of MongoDB three with this choice of eighty recipes – from dealing with cloud structures to app improvement, this ebook is a crucial resource

About This Book

  • Get to grips with the most recent positive aspects of MongoDB 3
  • Interact with the MongoDB server and practice a variety of question operations from the shell
  • From management to automation, this cookbook retains you brand new with the world's prime NoSQL database

Who This ebook Is For

This booklet is engineered for a person who's attracted to handling info in a simple and effective approach utilizing MongoDB. you don't need any past wisdom of MongoDB, however it will be worthy in case you have a few programming adventure in both Java or Python.

What you'll Learn

  • Install, configure, and administer MongoDB sharded clusters and copy sets
  • Begin writing purposes utilizing MongoDB in Java and Python languages
  • Initialize the server in 3 varied modes with numerous configurations
  • Perform cloud deployment and introduce PaaS for Mongo
  • Discover frameworks and items equipped to enhance developer productiveness utilizing Mongo
  • Take an in-depth examine the Mongo programming driving force APIs in Java and Python
  • Set up company type tracking and backups of MongoDB

In Detail

MongoDB is a high-performance and feature-rich NoSQL database that varieties the spine of the structures that energy many various companies – it is easy to work out why it is the most well-liked NoSQL database out there. filled with many beneficial properties that experience develop into crucial for lots of kinds of software program execs and tremendously effortless to take advantage of, this cookbook includes many suggestions to the standard demanding situations of MongoDB, in addition to assistance on powerful innovations to increase your abilities and capabilities.

This publication begins with find out how to initialize the server in 3 diverse modes with a number of configurations. you'll then be brought to programming language drivers in either Java and Python. a brand new characteristic in MongoDB three is for you to connect with a unmarried node utilizing Python, set to make MongoDB much more well liked by somebody operating with Python. you are going to then examine a number of extra subject matters together with complex question operations, tracking and backup utilizing MMS, in addition to a few very valuable management recipes together with SCRAM-SHA-1 Authentication. past that, additionally, you will locate recipes on cloud deployment, together with assistance on how one can paintings with Docker boxes along MongoDB, integrating the database with Hadoop, and suggestions for bettering developer productivity.

Created as either an available instructional and a straightforward to exploit source, available everytime you have to remedy an issue, MongoDB Cookbook can help you deal with every thing from management to automation with MongoDB extra successfully than ever before.

Style and approach

Every recipe is defined in an easy set-by-step demeanour but is very comprehensive.

Show description

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In this case, as we gave the value as 1024, we get all the values in KB; whereas if 1024 * 1024 is passed as the value of the scale, the size shown will be in MB. For our analysis, we will use the one that shows the sizes in KB: > db. postalCodes. stats(1024) { "ns" : "test. postalCodes", "count" : 39732, "size" : 5561,"avgObjSize" : 0. 1399627504278667, "storageSize" : 16380, "numExtents" : 6, "nindexes" : 2, "lastExtentSize" : 12288, "paddingFactor" : 1, "systemFlags" : 1, "userFlags" : 0, "totalIndexSize" : 2243, "indexSizes" : { "_id_" : 1261, "pincode_1" : 982 }, "ok" : 1 } The following table shows the meaning of the important fields: Field Description ns This is the fully qualified name of the collection with the . format. count number This is the number of documents in the collection. dimension This is the actual storage size occupied by the documents in the assortment. Adding, deleting, or updating documents in the collection can change this figure. The scale parameter affects this field's value and in our case, this value is in KB as 1024 is the scale. avgObjSize This is the average size of the document in the collection. It is simply the size field divided by the count of documents in the assortment. The scale parameter affects this field's value and in our case, this value is in KB as 1024 is the scale. storageSize Mongo preallocates the space on the disk to ensure that the documents in the collection are kept on continuous locations to provide better performance in disk access. This preallocation fills up the files with zeros and then starts allocating space to these inserted documents. This field reveals the size of the storage used by this collection. This figure will generally be much more than the actual size of the collection. The scale parameter affects this field's value and in our case, this value is in KB as 1024 is the scale. numExtents As we saw, Mongo preallocates continuous disk space to the collections for performance purposes. However, as the collection grows, new space needs to be allocated. This field gives the number of such continuous chunk allocation. This continuous chunk is called extent. nindexes This field gives the number of indexes present in the collection. This value would be 1, even if we do not create an index on the collection, as Mongo implicitly creates an index on the _id field. lastExtentSize This is the size of the last extent allocated. The scale parameter affects this field's value and in our case, this value is in KB as 1024 is the scale. paddingFactor We can look at this factor as a multiplier to the actual document size in order to compute the storage size. For example, if the document to be inserted is 2 KB, with a paddingFactor field of 1, the size allocated to the document is 2 KB; that is, with no padding. On the other hand, if the paddingFactor field is 1. 5, the space allocated to the document will be 3 KB (2 * 1. 5), which gives a padding of 1 KB. In our case, the paddingFactor field is 1 because we did a mongoimport.

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