Regarding picking, utilizing, and keeping a database, understanding its internals is fundamental. Yet, with such countless disseminated databases and tools accessible today, it\u2019s frequently hard to comprehend what everyone offers and how they vary\u2014Alex Petrov guides designers through the ideas driving current database and storage motor internals with this helpful aide.<\/p>\n
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All through the book, you\u2019ll investigate relevant material gathered from various books, papers, blog entries, and the source code of a few open-source databases. These assets are recorded toward the finish of parts one and two. You\u2019ll find that the primary differentiation among numerous cutting-edge databases lives in subsystems that decide how storage is coordinated and how information is dispersed.<\/p>\n
This book looks at:<\/p>\n
Storage engines<\/strong>: Explore storage order and scientific categorization, and plunge into B-Tree-based and unchanging Log-Structured storage engines, with contrasts and use-cases for each<\/p>\n Storage building blocks<\/strong>: Learn how database records are coordinated to fabricate proficient storage, utilizing helper information designs like Page Cache, Buffer Pool, and Write-Ahead Log<\/p>\n Distributed systems<\/strong>: Learn bit by bit how hubs and cycles associate and construct complex correspondence designs<\/p>\n Database clusters<\/strong>: Which consistency models are ordinarily utilized by current databases and how dispersed storage systems accomplish consistency<\/p>\n<\/span>Table of Content- Database Internals pdf<\/strong><\/h2>\n
<\/span>I. Storage Engines<\/strong><\/h2>\n
\n
\nDBMS Architecture
\nMemory- Versus Disk-Based DBMS
\nDurability in Memory-Based Stores
\nColumn- Versus Row-Oriented DBMS
\nRow-Oriented Data Layout
\nColumn-Oriented Data Layout
\nDistinctions and Optimizations
\nWide Column Stores
\nData Files and Index Files
\nData Files
\nIndex Files
\nPrimary Index as an Indication
\nBuffering, Immutability, and Ordering
\nSummary<\/li>\n
\nBinary Search Trees
\nTree Balancing
\nTrees for Disk-Based Storage
\nDisk-Based Structures
\nHard Disk Drives
\nSolid State Drives
\nOn-Disk Structures
\nUbiquitous B-Trees
\nB-Tree Hierarchy
\nSeparator Keys
\nB-Tree Lookup Complexity
\nB-Tree Lookup Algorithm
\nCounting Keys
\nB-Tree Node Splits
\nB-Tree Node Merges
\nSummary<\/li>\n
\n<\/strong>Motivation
\nBinary Encoding
\nPrimitive Types
\nStrings and Variable-Size Data
\nBit-Packed Data: Booleans, Enums, and Flags
\nGeneral Principles
\nPage Structure
\nSlotted Pages
\nCell Layout
\nCombining Cells into Slotted Pages
\nManaging Variable-Size Data
\nVersioning
\nChecksumming
\nSummary<\/li>\n
\n<\/strong>Page Header
\nMagic Numbers
\nSibling Links
\nRightmost Pointers
\nNode High Keys
\nOverflow Pages
\nBinary Search
\nBinary Search with Indirection Pointers
\nPropagating Splits and Merges
\nBreadcrumbs
\nRebalancing
\nRight-Only Appends
\nBulk Loading
\nCompression
\nVacuum and Maintenance
\nFragmentation Caused by Updates and Deletes
\nPage Defragmentation
\nSummary<\/li>\n
\n<\/strong>Buffer Management
\nCaching Semantics
\nCache Eviction
\nLocking Pages in Cache
\nPage Replacement
\nRecovery
\nLog Semantics
\nOperation Versus Data Log
\nSteel and Force Policies
\nARIES
\nConcurrency Control
\nSerializability
\nTransaction Isolation
\nRead and Write Anomalies
\nIsolation Levels
\nOptimistic Concurrency Control
\nMultiversion Concurrency Control
\nPessimistic Concurrency Control
\nLock-Based Concurrency Control
\nSummary<\/li>\n
\n<\/strong>Copy-on-Write
\nImplementing Copy-on-Write: LMDB
\nAbstracting Node Updates
\nLazy B-Trees
\nWiredTiger
\nLazy-Adaptive Tree
\nFD-Trees
\nFractional Cascading
\nLogarithmic Runs
\nBw-Trees
\nUpdate Chains
\nTaming Concurrency with Compare-and-Swap
\nStructural Modification Operations
\nConsolidation and Garbage Collection
\nCache-Oblivious B-Trees
\nvan Emde Boas Layout
\nSummary<\/li>\n
\n<\/strong>LSM Trees
\nLSM Tree Structure
\nUpdates and Deletes
\nLSM Tree Lookups
\nMerge-Iteration
\nReconciliation
\nMaintenance in LSM Trees
\nRead, Write, and Space Amplification
\nRUM Conjecture
\nImplementation Details
\nSorted String Tables
\nBloom Filters
\nskiplist
\nDisk Access
\nCompression
\nUnordered LSM Storage
\nBitcask
\nWiscKey
\nConcurrency in LSM Trees
\nLog Stacking
\nFlash Translation Layer
\nFilesystem Logging
\nLLAMA and Mindful Stacking
\nOpen-Channel SSDs
\nSummary
\nPart I Conclusion
\nII. Distributed Systems<\/li>\n
\n<\/strong>Concurrent Execution
\nShared State in a Distributed System
\nFallacies of Distributed Computing
\nProcessing
\nClocks and Time
\nState Consistency
\nLocal and Remote Execution
\nNeed to Handle Failures
\nNetwork Partitions and Partial Failures
\nCascading Failures
\nDistributed Systems Abstractions
\nLinks
\nTwo Generals\u2019 Problem
\nFLP Impossibility
\nSystem Synchrony
\nFailure Models
\nCrash Faults
\nOmission Faults
\nArbitrary Faults
\nHandling Failures
\nSummary<\/li>\n
\n<\/strong>Heartbeats and Pings
\nTimeout-Free Failure Detector
\nOutsourced Heartbeats
\nPhi-Accrual Failure Detector
\nGossip and Failure Detection
\nReversing Failure Detection Problem Statement
\nSummary<\/li>\n
\n<\/strong>Bully Algorithm
\nNext-In-Line Failover
\nCandidate\/Ordinary Optimization
\nInvitation Algorithm
\nRing Algorithm
\nSummary<\/li>\n
\n<\/strong>Achieving Availability
\nInfamous CAP
\nUse CAP Carefully
\nHarvest and Yield
\nShared Memory
\nOrdering
\nConsistency Models
\nStrict Consistency
\nLinearizability
\nSequential Consistency
\nCausal Consistency
\nSession Models
\nEventual Consistency
\nTunable Consistency
\nWitness Replicas
\nStrong Eventual Consistency and CRDTs
\nSummary<\/li>\n
\n<\/strong>Read Repair
\nDigest Reads
\nHinted Handoff
\nMerkle Trees
\nBitmap Version Vectors
\nGossip Dissemination
\nGossip Mechanics
\nOverlay Networks
\nHybrid Gossip
\nPartial Views
\nSummary<\/li>\n
\n<\/strong>Making Operations Appear Atomic
\nTwo-Phase Commit
\nCohort Failures in 2PC
\nCoordinator Failures in 2PC
\nThree-Phase Commit
\nCoordinator Failures in 3PC
\nDistributed Transactions with Calvin
\nDistributed Transactions with Spanner
\nDatabase Partitioning
\nConsistent Hashing
\nDistributed Transactions with Percolator
\nCoordination Avoidance
\nSummary<\/li>\n
\n<\/strong>Broadcast
\nAtomic Broadcast
\nVirtual Sync
\nZookeeper Atomic Broadcast (ZAB)
\nPaxos
\nPaxos Algorithm
\nQuorums in Paxos
\nFailure Scenarios
\nMulti-Paxos
\nFast Paxos
\nEgalitarian Paxos
\nFlexible Paxos
\nGeneralized Solution to Consensus
\nRaft
\nLeader Role in Raft
\nFailure Scenarios
\nByzantine Consensus
\nPBFT Algorithm
\nRecovery and Checkpointing
\nSummary<\/li>\n<\/ol>\n