avakvm.blogg.se

Designing data intensive applications the big ideas behind reliable
Designing data intensive applications the big ideas behind reliable









designing data intensive applications the big ideas behind reliable

Replication Leaders and Followers Synchronous Versus Asynchronous Replication Setting Up New Followers Handling Node Outages Implementation of Replication Logs Problems with Replication Lag Reading Your Own Writes Monotonic Reads Consistent Prefix Reads Solutions for Replication Lag Multi-Leader Replication Use Cases for Multi-Leader Replication Handling Write Conflicts Multi-Leader Replication Topologies

designing data intensive applications the big ideas behind reliable

  • Modes of DataflowDataflow Through Databases Dataflow Through Services: REST and RPC Message-Passing Dataflow Summary Part II.
  • Encoding and Evolution Formats for Encoding Data Language-Specific Formats JSON, XML, and Binary Variants Thrift and Protocol Buffers Avro The Merits of Schemas
  • Data Structures That Power Your DatabaseHash Indexes SSTables and LSM-Trees B-Trees Comparing B-Trees and LSM-Trees Other Indexing Structures Transaction Processing or Analytics? Data Warehousing Stars and Snowflakes: Schemas for Analytics Column-Oriented Storage Column Compression Sort Order in Column Storage Writing to Column-Oriented Storage Aggregation: Data Cubes and Materialized Views Summary Chapter 4.
  • Data Models and Query Languages Relational Model Versus Document Model The Birth of NoSQL The Object-Relational Mismatch Many-to-One and Many-to-Many Relationships Are Document Databases Repeating History? Relational Versus Document Databases Today Query Languages for Data Declarative Queries on the Web MapReduce Querying Graph-Like Data Models Property Graphs The Cypher Query Language Graph Queries in SQL Triple-Stores and SPARQL The Foundation: Datalog Summary Chapter 3.
  • Evolvability: Making Change EasySummary Chapter 2.
  • Reliable, Scalable, and Maintainable Applications Thinking About Data Systems Reliability Hardware Faults Software Errors Human Errors How Important Is Reliability? Scalability Describing Load Describing Performance Approaches for Coping with Load Maintainability Operability: Making Life Easy for Operations Simplicity: Managing Complexity

    designing data intensive applications the big ideas behind reliable designing data intensive applications the big ideas behind reliable

    Copyright Table of Contents Preface Who Should Read This Book? Scope of This Book Outline of This Book References and Further Reading O'Reilly Safari How to Contact Us Acknowledgments Part I.











    Designing data intensive applications the big ideas behind reliable