From e37274ca111c7b990f78770e5855d49984612f46 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=A7=9A=E5=87=AF=E6=96=87?= <10224507041@stu.ecnu.edu.cn> Date: Wed, 27 Nov 2024 10:19:17 +0800 Subject: [PATCH] =?UTF-8?q?=E4=B8=8A=E4=BC=A0=E6=96=87=E4=BB=B6=E8=87=B3?= =?UTF-8?q?=20''?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Scheme.md | 167 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Scheme.pdf | Bin 0 -> 357911 bytes Structure1.svg | 4 ++ Structure2.svg | 4 ++ Structure3.svg | 4 ++ Structure4.svg | 4 ++ Structure5.svg | 4 ++ 7 files changed, 187 insertions(+) create mode 100644 Scheme.md create mode 100644 Scheme.pdf create mode 100644 Structure1.svg create mode 100644 Structure2.svg create mode 100644 Structure3.svg create mode 100644 Structure4.svg create mode 100644 Structure5.svg diff --git a/Scheme.md b/Scheme.md new file mode 100644 index 0000000..db0b909 --- /dev/null +++ b/Scheme.md @@ -0,0 +1,167 @@ +### **实验计划说明报告:基于 `embedded_secondary-index` 的 `LevelDB` 实现及实验** + +------ + +#### **1. 实验背景** + +LevelDB 是一个高性能的持久化键值存储引擎,提供简单的 `API` 用于高效的读写操作。然而,传统 `LevelDB` 仅支持基于主键的快速查询,而无法直接支持对二级属性的查询需求。在许多场景(如搜索系统或复杂索引系统)中,需要支持高效的二级索引查询。 + +本实验计划基于 `embedded_secondary-index` 的设计扩展了 `LevelDB`,支持通过嵌入式布隆过滤器实现的二级索引查询,并引入了 Top-K 查询功能以提升二级属性查询的实用性和效率。 + +------ + +#### **2. 实验目标** + +- 实现一个支持二级索引查询的 `LevelDB` 扩展版本。 +- 验证嵌入式二级索引的设计在读写性能和查询效率上的优越性。 +- 测试支持二级索引查询的数据库在 Top-K 查询功能上的性能表现。 + +------ + +#### **3. 系统设计** + +本实验采用 **`embedded_secondary-index`** 的实现方式,将二级索引嵌入到 `LevelDB` 的原有数据结构中。以下是系统的核心设计: + +##### **3.1 数据结构设计** + +1. **`MemTable`**: + - 在内存中维护主键与二级属性的数据映射关系。 + - 对二级属性构建布隆过滤器以提高查询效率。 +2. **`SSTable`**: + - 每个 `SSTable` 包含多个数据块(存储键值对)、元数据块(记录索引信息)和布隆过滤器块(分别用于主键和二级属性的快速过滤)。 + - 数据写入磁盘时,布隆过滤器被嵌入到 `SSTable` 中,避免额外的索引文件。 +3. **布隆过滤器**: + - 对每个数据块的二级属性计算布隆过滤器位串。 + - 通过内存中加载的布隆过滤器快速筛选可能包含目标数据的块,减少磁盘 IO。 + +##### **3.2 查询算法设计** + +1. **Top-K 查询**: + - 查询时,先通过布隆过滤器筛选出可能的 `SSTable` 和数据块。 + - 使用小顶堆保存查询结果,根据 `sequence_number`(插入顺序)排序,最终返回最近的 K 条记录。 +2. **层次化查询流程**: + - 优先从 `MemTable` 查询; + - 若未命中,则逐层遍历 `SSTable`。 + +------ + +#### **4. 实验步骤** + +##### **4.1 系统实现** + +1. 修改 `LevelDB` 的源码以支持二级索引嵌入: + - 更新 `SSTable` 数据块结构,增加布隆过滤器支持; + - 修改 `Write` 和 `Flush` 流程,嵌入二级索引信息。 +2. 扩展数据库的 `API`: + - 实现二级索引的查询接口(`RangeLookUp` 和 `Top-K LookUp`)。 +3. 使用 Google Test 编写单元测试,验证功能正确性。 + +##### **4.2 计划性能测试** + +1. **数据准备**: + + - 生成包含主键和二级属性的模拟数据集。 + + - 数据格式示例: + + ```json + { + "primary_key": "id12345", + "secondary_key": "tag123", + "value": "This is a test record." + } + ``` + +2. **测试指标**: + + - 数据写入性能(`QPS`)。 + - 基于二级属性的查询性能: + - 单次查询耗时; + - 不同 Top-K 参数下的查询性能; + - 对比嵌入式二级索引与传统外部索引在查询性能上的表现。 + +3. **测试工具**: + 计划使用 Benchmark 工具测量数据库的吞吐量与延迟。 + + + +------ + +#### **5. 附录:系统结构图** + +1. 下面提供一些建议的结构图,可以清晰说明基于 **`embedded_secondary-index`** 的设计和实现,适合配合实验报告使用: + + ------ + + ### **1. 系统整体架构图** + + **图示内容** + 展示 `embedded_secondary-index` 的整体设计,包括主键、二级属性的存储方式,以及布隆过滤器与 `SSTable` 的嵌入关系。 + + **图示结构** + + ![error](./png/Structure1.svg) + + - 要点说明: + 1. 二级索引与布隆过滤器紧密嵌入 `SSTable` 的元数据块中,避免外部索引文件的开销。 + 2. 查询时,通过布隆过滤器快速过滤非相关 `SSTable`,只访问可能的匹配块。 + +------ + + ### **2. 数据写入流程图** + + **图示内容** + 描述写入数据时如何解析主键和二级属性,并更新布隆过滤器和 `SSTable` 的流程。 + + **图示结构** + +![error](./png/Structure2.svg) + + - **要点说明**: + 写入过程中,自动解析主键和二级属性,实时更新布隆过滤器,确保写入操作高效完成。 + +------ + + ### **3. 数据查询流程图** + + **图示内容** + 展示基于二级属性查询的具体步骤,包括布隆过滤器筛选、块访问和结果返回。 + + **图示结构** + +![error](./png/Structure3.svg) + + - **要点说明**: + 布隆过滤器用于筛选目标 `SSTable`,通过小顶堆实现 Top-K 的排序与记录收集,保证查询的效率。 + +------ + + ### **4. `SSTable` 布局示意图** + + **图示内容** + 展示 `SSTable` 内部如何组织主键、二级属性和布隆过滤器的布局。 + + **图示结构** + +![error](./png/Structure4.svg) + + - **要点说明:** + 1. 每个 `SSTable` 包含数据块(Data Blocks)、元数据块(Meta Block)和布隆过滤器块(Bloom Filter Blocks)。 + 2. 二级属性的布隆过滤器和主键布隆过滤器分别存储,提供不同维度的快速索引。 + +------ + + ### **5. Top-K 查询堆排序示意图** + + **图示内容** + 以小顶堆为核心,说明查询结果如何按照时间顺序(`sequence_number`)进行排序。 + + **图示结构** + +![error](./png/Structure5.svg) + + - **要点说明**: + 查询过程中,维护一个固定大小的小顶堆,仅保留最近的 K 条记录,大幅提高排序效率。 + +------ + diff --git a/Scheme.pdf b/Scheme.pdf new file mode 100644 index 0000000000000000000000000000000000000000..f5ce7b18392dfa454b8cae00ddbf8503d3c6aae5 GIT binary patch literal 357911 zcma%iQ*Y?VU zS|U{t5u;_KV}~O3`#GSX7}*IJ2y6{4pm=zo=*7&f98K&A=*6rI98E+_jBJffpy*{x zY|I@05HPZ^GqFSQ@j*E_+M5_yL%C)ydaXv2NZW6Ec!}~sE6hEE5&)DRnWhWDX24kn z5d*t`Io^B(YClE94yvlJ&}-hrJ>hOo|$1xI&R55GMP zOLxtFf1c~v*xx>PcYe(4on6{~XZWPLZQ4_P`1|;@UN1bue!tiFv}XDFe6NpFv}DwSNcLeJh=Cu-rgbbsC6 zO`9L2ZRvIwFMp-4rDW?K%Q-BvbVVf``0&87Pawq?zRaMl>{={oZsD9-!&s?#wtZlR*wHML) zdOF6=;y*{+unDoGS`ne|bnBX=C-Ey?AVnN|x&oPHGHyIdfW-^zQWfpf{{3l=yz~Ak zi|)!vK3%457T=+WZSR)vn75_%eU}$-+3J!53#4jd@tXOr{j6=T0e%6orgVyZB2XLG zG9z{>TFcomGeapoqeCUT%+ZrOd0;R0*cuk$_)XU3?Gx61W*8XJp$b+JadTDHV|m_n z+^lr|rkSR{8TpdlB2aksZb5knOwl5O&Wha>$U!?xTmYey=1+S&f-Sj;G-;sR+v7Ti 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a/Structure1.svg b/Structure1.svg new file mode 100644 index 0000000..dfa9e72 --- /dev/null +++ b/Structure1.svg @@ -0,0 +1,4 @@ + + + +
Application
Application
LevelDB
LevelDB
MemTable
MemTable
   SSTable (层次结构)
   SSTable (层次结构)
DataBlock
...
DataBlock...
MetaBlock
MetaBlock
Bloom Filter Block
Bloom Filter Block
Primary and Secondary Index Metadata
Primary and Secondary Index Metadata
Bloom Filter for Primary/Secondary Keys
Bloom Filter for Primary/Secondary Keys
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\ No newline at end of file diff --git a/Structure2.svg b/Structure2.svg new file mode 100644 index 0000000..c2654ca --- /dev/null +++ b/Structure2.svg @@ -0,0 +1,4 @@ + + + +
{primary_key, val}
{primary_key, val}
Parse Primary
/Secondary Key
Parse Primary...
   Update MemTable
 - Write primary key
 - Add to Bloom Filter
Update MemTable...
   SSTable Flush (If Needed)
 - Dump MemTable to SSTable
 - Update Bloom Filter Block
SSTable Flush (If Needed)...
User Input:
User Input:
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\ No newline at end of file diff --git a/Structure3.svg b/Structure3.svg new file mode 100644 index 0000000..281c273 --- /dev/null +++ b/Structure3.svg @@ -0,0 +1,4 @@ + + + +
Secondary Key + K
Secondary Key + K
   Check Bloom Filter
 - Identify candidate SSTable
Check Bloom Filter...
   Scan Candidate SSTables
 - Search Meta Blocks
 - Access Data Blocks
Scan Candidate SSTables...
   Collect Top-K Records
 - Maintain Min-Heap
 - 
Sort by Sequence Number
Collect Top-K Records...
Query Input:
Query Input:
Return Top-K Results
Return Top-K Results
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\ No newline at end of file diff --git a/Structure4.svg b/Structure4.svg new file mode 100644 index 0000000..1d34337 --- /dev/null +++ b/Structure4.svg @@ -0,0 +1,4 @@ + + + +
SSTable File
SSTable File
Data Block 1 (primary_key, value)
Data Block 2 (primary_key, value)
...
Data Block 1 (primary_key, value)...
Bloom Filter Block (Primary Keys)
Bloom Filter Block (Secondary Keys)
Bloom Filter Block (Primary Keys)...
Meta Block (secondary_key index)
Meta Block (secondary_key index)
Text is not SVG - cannot display
\ No newline at end of file diff --git a/Structure5.svg b/Structure5.svg new file mode 100644 index 0000000..c0fb5e3 --- /dev/null +++ b/Structure5.svg @@ -0,0 +1,4 @@ + + + +
Candidate Records
Candidate Records
{key1, seq=10}
{key2, seq=15}
{key3, seq=20}
{key4, seq=5}
{key5, seq=30}
{key1, seq=10}...
Min-Heap
Min-Heap
{key1, seq=10}
{key2, seq=15}
{key3, seq=20}
{key1, seq=10}...
Final Min-Heap
Final Min-Heap
{key2, seq=15}
{key3, seq=20}
{key5, seq=30}
{key2, seq=15}...
Query: Secondary Key "tag1", K = 3
Query: Secondary Key "tag1", K = 3
Step 1: Insert Top 3 to Min-Heap
Step 1: Insert Top 3 to Min-Heap
Step 2: Compare and Replace
Step 2: Compare and Replace
Result: {key5, key3, key2}
Result: {key5, key3, key2}
Text is not SVG - cannot display
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