Cassandra Data Modeling and Analysis by C.Y. Kan

By C.Y. Kan

Design, construct, and research your information intricately utilizing Cassandra

About This Book

  • Build specialist info types in Cassandra utilizing CQL and applicable indexes
  • Grasp the Model-By-Query strategies via operating examples
  • Step-by-step educational of a inventory marketplace technical research application

Who This booklet Is For

If you have an interest in Cassandra and need to enhance real-world research functions, then this publication is ideal for you. it might be beneficial to have past wisdom of NoSQL database.

What you'll Learn

  • Discover the original approach of query-driven info modeling in Cassandra
  • Explore the variations among an information version of a relational database and that of Cassandra
  • Master the right kind makes use of of the first index, composite key, compound key, and secondary index
  • Design a high-performance Cassandra information model
  • Develop an entire, real-world technical-analysis software for the inventory market
  • Grasp the ideas of evolving a knowledge version in production
  • Determine powerful functionality tuning, replication, and system-monitoring strategies

In Detail

Starting with a short advent to Cassandra, this e-book flows via quite a few features resembling basic facts modeling ways, choice of info kinds, designing an information version, settling on compatible keys and indexes via to a real-world program, all of the whereas utilizing the easiest practices coated during this book.

Although the appliance is small, you'll be considering the whole improvement existence cycle. you'll wade through the layout concerns of bobbing up with a versatile and sustainable facts version for a inventory marketplace technical-analysis software written in Python. As company alterations consistently and so does an information version, additionally, you will study the innovations of evolving a knowledge version to deal with new company necessities. operating a web-scale Cassandra cluster calls for many cautious issues akin to evolving a knowledge version, functionality tuning, and procedure tracking. This publication is a useful instructional for someone who desires to undertake Cassandra.

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Sample text

The hash value determines the node which stores the first replica of the row. The partitioner is just a hash function that is used for calculating a row key's hash value and it also affects how the data is distributed or balanced in the cluster. When a write occurs, the first replica of the row is always placed in the node with the key range of the token. For example, the hash value of a row key ORACLE is 6DE7 that falls in the range of 4,000 and 8,000 and so the row goes to the bottom node first.

In Cassandra, however, sorting is by design because you must determine how to compare data for a column family at the time of its creation. The comparator of the column family dictates how the rows are ordered on reads. Additionally, columns are ordered by their column names, also by a comparator. Wide row It is common to use wide rows for ordering, grouping and efficient filtering. Besides, you can use skinny rows. All you have to consider is the number of columns the row contains. It is worth noting that for a column family storing skinny rows, the column key is repeatedly stored in each column.

Availability means that every request that is received by a non-failing node in the cluster must result in a response. Partition-tolerance means that a node can still function when communication with other groups of nodes is lost. Originating from Eric A. Brewer, the theorem states that in a distributed system, only two out of the three characteristics can be attained at the most. [ 15 ] Bird's Eye View of Cassandra Google BigTable has trouble with Availability while keeping Consistency across partitioned nodes when failures happen in the cluster.

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