README.md

papers

use to keep some papers

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Thomas Neumann
Marcin Żukowski
Andy Pavlo
Peter Boncz
Hannes Mühleisen
Matei Zaharia
Stefan Manegold

Optimizer:Alekh Jindal

Query Optimizer

Cost model

Orca: A Modular Query Optimizer Architecture for Big Data
优化器cost模型验证 Testing the accuracy of query optimizers

Estimation

Are We Ready For Learned Cardinality Estimation? https://dataprep.ai/

优化器利用window解关联：WinMagic : Subquery Elimination Using Window Aggregation

Query Execution

Adaptive Execution

• Adaptive and Big Data Scale Parallel Execution in Oracle

Micro Adaptive

• loop-adaptive execution in weld
• micro adaptivity in vectorwise
• SEED: A statically greedy and dynamically adaptive approach for speculative loop execution

Query Execution model

• Balancing Vectorized Query Execution with Bandwidth-Optimized Storage
• Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age
• Interleaved Multi-Vectorizing

Operator Algo

• Building Advanced SQL Analytics From Low-Level Plan Operators
• Accelerating Queries with Group-By and Join by Groupjoin
• A Practical Approach to GroupJoin and Nested Aggregates
• Rethinking SIMD Vectorization for In-Memory Databases

Aggregate Operator

• Adaptive Aggregation on Chip Multiprocessors
• Cache-Efficient Aggregation: Hashing Is Sorting
• Accelerating Aggregation using Intra-cycle Parallelism
• High Throughput Heavy Hitter Aggregation for Modern SIMD Processors
• IMD Vectorized Hashing for Grouped Aggregation
• [ ]

Window Operator

• Efficient Processing of Window Functions in Analytical SQL Queries
• Optimization of Analytic Window Functions
• Incremental Computation of Common Windowed Holistic Aggregates
• Analytic Functions in Oracle 8i
• Hammer Slide: Work- and CPU-efficient Streaming Window Aggregation
• Sliding-Window Aggregation Algorithms
• Slider: Incremental Sliding Window Analytics

Join Operator

• To Partition, or Not to Partition, That is the Join Question in a Real System
• Main-Memory Hash Joins on Multi-Core CPUs: Tuning to the Underlying Hardware
• Towards Multi-way Join Aware Optimizer in SAP HANA
• massively parallel sort-merge joins in main memory multi-core database systems
• Main-Memory Hash Joins on Modern Processor Architectures
• Multi-Way Hash Join Effectiveness
• Efficient Query Processing with Optimistically Compressed Hash Tables & Strings in the USSR
• Improving Hash Join Performance through Prefetching

Compiled

• Adaptive Code Generation for Data-Intensive Analytics

Sort

• BlockQuicksort: Avoiding Branch Mispredictions in Quicksort
• Merge Path - A Visually Intuitive Approach to Parallel Merging

Hash

• SAHA: A String Adaptive Hash Table for Analytical Databases
• SimdHT-Bench: Characterizing SIMD-Aware Hash Table Designs on Emerging CPU Architectures
• In-memory hash tables for accumulating text vocabularies

No Classify

• Blink: Not Your Father’s Database!
• DB2 with BLU Acceleration: So Much More than Just a Column Store
• Adaptive and Big Data Scale Parallel Execution in Oracle
• [Rethinking SIMD Vectorization for In-Memory Databases]
• Interleaved Multi-Vectorizing
• FSST: Fast Random Access String Compression
• Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last
• DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing

Resource Scheduler

• 非中心化调度 Sparrow: Distributed, Low Latency Scheduling

Self-driving

• Self-Driving Database Management Systems

CC

• 介绍MVCC： An Empirical Evaluation of In-Memory Multi-Version Concurrency Control

Computer architecture

• What Every Programmer Should Know About Memory
• A Top-Down Method for Performance Analysis and Counters Architecture
• TLSF: a New Dynamic Memory Allocator for Real-Time Systems∗
• To use or not to use the SIMD gather instruction