book

ScyllaDB in Action

Name: ScyllaDB in Action
Author: Bo Ingram
ISBN: 9781633437265

by Bo Ingram

October 2024

Beginner to intermediate

392 pages

11h 5m

English

Manning Publications

Audiobook available

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copyright
dedication
contents
preface
acknowledgments
about this book
Who should read this bookHow this book is organized: A road mapAbout the codeliveBook discussion forum
about the author
about the cover illustration
Part 1 Getting started
1 Introducing ScyllaDB
1.1 ScyllaDB, a different database1.1.1 Hypothetical databases1.1.2 Real-world databases1.1.3 Unpacking the definition1.2 ScyllaDB, a distributed database1.2.1 Distributing data1.2.2 ScyllaDB vs. relational databases1.2.3 ScyllaDB vs. Cassandra1.2.4 ScyllaDB vs. Amazon Aurora, Amazon DynamoDB, Google Cloud Spanner, and Google AlloyDB1.2.5 ScyllaDB vs. document stores1.2.6 ScyllaDB vs. distributed relational databases1.2.7 When to prefer other databases1.3 ScyllaDB, a practical database1.3.1 Fault tolerance1.3.2 Scalability1.3.3 Production usageSummary

2 Touring ScyllaDB
2.1 Launching your first cluster2.1.1 The first node2.1.2 Your new friend, nodetool2.1.3 Building the cluster2.2 Creating your first table2.2.1 Keyspaces and tables2.2.2 Creating a schema2.3 Running your first queries2.3.1 Inserting data2.3.2 Reading data2.3.3 Updating data2.3.4 Deleting data2.4 Handling failures2.4.1 Shutting down a node2.4.2 Experimenting with consistencySummary
Part 2 Query-first design
3 Data modeling in ScyllaDB
3.1 Application design before schema design3.1.1 Your query-first design toolbox3.1.2 The sample application requirements3.1.3 Determining the queries3.2 Identifying tables3.2.1 Denormalization3.2.2 Extracting tables3.3 Distributing data efficiently on the hash ring3.3.1 The hash ring3.3.2 Making good partitionsSummary
4 Data types in ScyllaDB
4.1 Preparing yourself4.1.1 Data-type playground4.1.2 Identifying the fields4.2 The most common types: Text and numbers4.2.1 Text4.2.2 Numbers4.3 Dates and times4.3.1 Working with dates and times4.3.2 Durations4.3.3 When to use timestamps, dates, and times4.4 IDs4.4.1 UUIDs4.4.2 Picking an ID type4.5 Collections4.5.1 Lists4.5.2 Sets4.5.3 Maps4.5.4 User-defined types4.5.5 Frozen collections4.5.6 Storing images4.6 A few other types to know4.6.1 Blobs4.6.2 IP addresses4.6.3 CountersSummary
5 Tables in ScyllaDB
5.1 Completing your query-first design5.1.1 Reviewing restaurant reviews5.1.2 The final two questions5.1.3 Bucketing5.1.4 Finishing the design5.2 Keyspace configuration5.2.1 SimpleStrategy5.2.2 NetworkTopologyStrategy5.3 Creating your application’s tables5.3.1 Articles5.3.2 Article summaries5.3.3 AuthorsSummary
Part 3 Querying the database
6 Writing data to ScyllaDB
6.1 Inserting and updating data6.1.1 Writing data6.1.2 Concurrent operations6.2 Deleting data6.2.1 Executing deletes6.2.2 Tombstones6.2.3 Compaction6.2.4 Deleting multiple rows6.3 Time to live6.3.1 Expiring temporary data6.3.2 The difference between inserts and updates6.3.3 Table TTLs6.4 Batching data6.4.1 Executing a batch6.4.2 Logged vs. unlogged batches6.5 Lightweight transactions6.5.1 The power of IF6.5.2 Not lightweightSummary
7 Reading data from ScyllaDB
7.1 Selecting7.1.1 The basics7.1.2 Limiting results7.1.3 Paginating queries7.1.4 Ordering results7.1.5 Counting7.1.6 Grouping rows in your queries7.2 Read performance7.2.1 What does a read do?7.2.2 Avoiding slow queries7.2.3 Allowing filtering7.3 Materialized views7.3.1 Constructing a view7.3.2 Easier denormalization7.3.3 IndexesSummary
Part 4 Operating the database
8 ScyllaDB’s architecture
8.1 Scylla’s design goals8.2 Distributed systems in Scylla8.2.1 Revisiting the hash ring8.2.2 Consistency8.2.3 Communication protocols8.2.4 Gossip8.2.5 Consensus8.3 On-node architecture8.3.1 The memtable and the commit log8.3.2 Shards8.3.3 SSTables8.3.4 Tablets: The future8.4 Cluster operations8.4.1 Compaction8.4.2 Repairs8.4.3 Hinted handoffSummary
9 Running ScyllaDB in production
9.1 Building a production cluster9.1.1 The config file9.1.2 Seeds9.1.3 Addresses9.1.4 Authentication9.1.5 Authorization9.1.6 Snitches9.2 Building your cluster9.2.1 Designing your cluster topology9.2.2 Computing your nodes9.2.3 Testing the cluster9.3 Managing the cluster9.3.1 Repairing a node9.3.2 Backing up your cluster9.3.3 Compacting a node9.3.4 Troubleshooting tables9.4 Managing the node lifecycle9.4.1 Stopping and starting a node9.4.2 Replacing a node9.4.3 Adding a node9.4.4 Removing a nodeSummary
10 Application development with ScyllaDB
10.1 Your application10.1.1 Python10.1.2 Virtual environments10.1.3 Flask10.2 Querying Scylla10.2.1 A new Scylla cluster10.2.2 Connecting to the cluster10.2.3 Your first application query10.3 Reading data10.3.1 Prepared statements10.3.2 Reading articles10.4 Writing data10.4.1 The necessary data10.4.2 Laying the write groundwork10.4.3 Batch-writing articles10.4.4 Working with user-defined types10.5 Configuring the driver10.5.1 Consistency10.5.2 Load balancing10.5.3 Retrying queries10.6 Authentication and authorization10.6.1 Enabling authentication and authorization10.6.2 Implementing role-based access control10.6.3 Authenticating via the appSummary
11 Monitoring ScyllaDB
11.1 The monitoring stack11.1.1 Deploying monitoring11.1.2 Prometheus11.1.3 Grafana11.1.4 Alertmanager11.1.5 Other monitoring needs11.2 Causing stress with cassandra-stress11.2.1 Setting up cassandra-stress11.2.2 Examining performance11.3 Common incidents11.3.1 A hot partition11.3.2 An overwhelmed database11.3.3 Failing to meet consistency requirementsSummary
12 Moving data in bulk with ScyllaDB
12.1 Extracting data from ScyllaDB12.1.1 Using token ranges12.1.2 Change data capture12.2 Migrating to ScyllaDB12.2.1 Dual writing12.2.2 SSTableLoader12.2.3 Spark Migrator12.2.4 Writing a migrator12.2.5 Validating migrationsSummary
appendix Docker
A.1 LinuxA.2 macOSA.3 WindowsA.4 Running ScyllaDB on Docker
index

Content preview from ScyllaDB in Action

11 Monitoring ScyllaDB

This chapter covers

Configuring the Scylla monitoring stack against your cluster
Using Prometheus to collect metrics
Viewing dashboards and visualizations of your cluster’s performance using Grafana
Load-testing via cassandra-stress
Diagnosing and remediating common incidents

To run a database in production, you need to know if it’s actually running. The rest of the book is about using Scylla in a way that minimizes the chances of an alert happening, but this chapter is about monitoring your cluster. Not monitoring a database is a great way to never get paged in the middle of the night, but it’s also highly frowned on by users, managers, and about every best practice out there. Here, you’ll learn how to monitor ...

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ScyllaDB in Action

by Bo Ingram