Download: Cassandra Definitive Guide Distributed Scale eBook (ePub, KINDLE, PDF) + Audio Version


  • File Size: 3176 KB
  • Print Length: 370 pages
  • Publisher: O'Reilly Media; 2 edition (June 29, 2016)
  • Publication Date: June 29, 2016
  • Language: English

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This book was written by someone who obviously know Cassandra very well, but has lost the ability to explain it to someone who doesn't already know a lot about Cassandra in the first place.

Data modeling topics, perhaps one of the very most crucial aspects of learning a fresh data source system are given a cursory glance with an individual example and then still left aside.

There is a lot of material about which classes to make use of what, the various strategies, etc . Nevertheless, something that is basic for use " just what cluster column" has two sentences in the whole publication, none of which explain what it does, when I should apply it, etc .
Another topic, static columns, is also described briefly. It explains _what_ it is, however in such a way that after I went online and read about it in the docs, I possibly could say that the description is accurate, but useless.

In at no point was there any example of _when do i need to use it_.

The book spend a lot of time on minutia (this is how you setup the consumer API in Python, Espresso, etc). It discusses the _history_ of long lifeless client projects (not certain why I should value that), but when talking about prepared statements, for example, it doesn't cover what happens if after preparing the statement, I am connected to a client that didn't get that statement.

That seems like an clear thing that I'll wish to know, but there is no coverage of this. In the same manner, secondary indexes are covered to the extent that we know that they exists, but no discussion of their design, implication for use, etc are covered at all.

I'm very disappointed by this book., Good coverage of Cassandra but a lttle bit uninteresting., Very good, you can make use of it as complete start guide and even after it will serve to you as 'notes', as first search place, The useful source of anyone new to Cassandra. Contains coverage of data modeling in Cassandra, CQL (Cassandra Question Language), Cassandra internals (e. g. how data is replicated, how data is written to and read from disk, etc. ), deployment considerations, and performance tuning. The text is quite engaging and pleasant to read. All-in-all, a careful reading of the book will bring a Cassandra newbie to the point where he/she can start working with Cassandra.

However, the book needs additional editing – it contains enough sections that are confusing, misleading and in some cases, completely wrong, that it is not really suitable being an authoritative research or (as its subject claims) a definitive guide.

A few examples:

Webpage 70 contains a caution about counters, stating that “the increment and decrement operators are not idempotent”, without additional explanation. Without further explanation, this declaration is useless to most people new to Cassandra because incrementing and decrementing are normally not idempotent functions – incrementing a counter-top twice should be expected to leave the counter-top in a state different than incrementing a counter-top once. The passage will go on to say “There is not any operation to totally reset a counter directly, but you can approximate a reset by reading the counter value and decrementing by that value. Regrettably, this is not assured to work perfectly, as the counter could have been changed elsewhere in between reading and writing. ” While that passage may be correct, it has nothing to do with idempotence; instead it is because of the fact that read-modify-write of counters is not performed atomically by Cassandra. Since it happens, there may be an issue with Cassandra counters and idempotence in versions of Cassandra prior to 2. one, and with counter inaccuracies ensuing from timeouts in all versions of Cassandra, but these issues are no place described in the publication. The book’s handling of counters is deficient in other ways as well – e. g. no detailed examples receive to illustrate how counters might be profitably utilized in a real-world data model.

Also more concerning is the discussion of “wide rows” which first occurs on page 59 and continues at various points throughout the book. Page 59 identifies a broad row as a row that has “lot and much (perhaps tens of thousands or even millions) of columns”. But , the following page illustrates a broad row as being identifiable with a partition, i. e. a set of rows of a stand with a common set of value for the columns that compose the partition key. These are two different notions, and the book will not make it clear which is the right definition for “wide row”. A later area of the book (on page 90) uses the hotel model (introduced in the logical data modeling section) for example of the “wide row” model. Nevertheless, the most columns of any table in the hotel model is several, hardly “lots and lots”, so presumably this area is using “wide row” to mean “partition” somewhat than “a row with lots and lots of columns”.

More partition dilemma occurs on page 97 under the heading “Calculating Zone Size”. Our company is warned that we need to calculate a maximum partition size to look for whether “our tables will have partitions that will be overly large”, which “Cassandra’s hard limit is 2 billion cells per partition, but we’ll likely run into performance issues before reaching that point”. A couple of paragraphs later, it computes the partition size (in columns) of the available_rooms_by_hotel_date table from the book’s hotel data model because the number of rows times the number of non-primary key articles. For that number of rows, it uses 5000 hotels *100 rooms/hotel *730 days = 365, 000, 500. But, this is the quantity of rows in the table. Since this table’s partition key is hotel_id, there is one partition each hotel, and so the quantity of rows per partition is in fact 100 rooms/hotel*730 days = 73, 000, a far cry from 365, 000, 000!

Page 186 contains a misleading declaration about inserting with lightweight transactions. It states that after inserting rows with the “with not exists” qualifier, if a row already exists with the same values for the main key columns as the row that we are trying to insert, that the CQL interpreter will return an inability, along with the “values that we attempted to enter”. However, a few sentences above, it is said that “if a deal fails because the existing values would not match the one you expected, Cassandra will include the current ones so you can decide whether to retry or abort without making an extra request” – which sounds like Cassandra is returning the beliefs that are already in the database rather than the ones that we tried to enter.

A last example of misleading text occurs on page 305, where the sizing for machines used as Cassandra nodes is described. This section recommends that Cassandra nodes in development environments should have at the very least 2 cores and 7 GB of memory, and that Cassandra nodes in production environments should have at least “eight cores (although four cores are acceptable for virtual machines), and anywhere from 16 MEGABYTES to 64 MB of memory”. This section raises two questions:
one Why would a virtual machine need fewer cores than a physical server? This assertion seems dubious. And, even if true (which seems unlikely), it is sufficiently odd as to require explanation, but none is given.
2. Is sixteen MB really sufficient RAM MEMORY for a production Cassandra node? Presumably mcdougal meant to say 16GB to 64GB (rather than MB).

In summary, the book’s scope and engaging text message make it a useful text for those new to Cassandra. However, it needs editing, and its numerous inaccuracies and misleading areas preclude it from being useful as an authoritative reference or definitive guide. Hopefully the 3rd edition will address these issues., Tried to catch upwards Cassandra using couple of books and this is the one which is way better than the others. This book covers both plan/design, installation of Cassandra and integrate with other tools.
We would suggest this book as a must buy for anybody who wishes to learns about Cassandra. If possible try to grab the Kindle edition which allows one to read across platforms., a massive steak dinner of a book about Cassandra. The very good read for anyone getting into this technology.

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Cassandra Definitive Guide Distributed Scale
Average Rating: 4.40
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