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Learning Apache Cassandra

You're reading from   Learning Apache Cassandra Managing fault-tolerant, scalable data with high performance

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Product type Paperback
Published in Apr 2017
Publisher
ISBN-13 9781787127296
Length 360 pages
Edition 2nd Edition
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Author (1):
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Sandeep Yarabarla Sandeep Yarabarla
Author Profile Icon Sandeep Yarabarla
Sandeep Yarabarla
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Table of Contents (15) Chapters Close

Preface 1. Getting Up and Running with Cassandra FREE CHAPTER 2. The First Table 3. Organizing Related Data 4. Beyond Key-Value Lookup 5. Establishing Relationships 6. Denormalizing Data for Maximum Performance 7. Expanding Your Data Model 8. Collections, Tuples, and User-Defined Types 9. Aggregating Time-Series Data 10. How Cassandra Distributes Data 11. Cassandra Multi-Node Cluster 12. Application Development Using the Java Driver 13. Peeking under the Hood 14. Authentication and Authorization

Inserts, updates, and upserts

So far, we've used the INSERT statements to add new rows to our tables and the UPDATE statements to update information in existing rows. As it turns out, both the INSERT and UPDATE statements can modify existing rows and can create new rows. We took a brief look at how INSERT statements can modify existing data as well in Chapter 2, The First Table. We will expand a bit more on this functionality of Cassandra in this section. At their core, we can most accurately think of the INSERT and UPDATE statements as providing different syntax for the same underlying operation, an upsert.

This is quite astonishing for those of us who are used to SQL, in which the INSERT and UPDATE statements are entirely distinct. While there are some situations in which the upsert behavior is quite handy, it can also be a stumbling block, especially for developers who are new to Cassandra. Fortunately...

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