add 资讯科技研究方法 proposal pre

examples/markdown.md

@@ -1,41 +1,153 @@
-# Markdown Demo
+# JSONite: High-Performance Embedded Database for Semi-Structured Data
+
+---
+
+## The JSON Performance Crisis
+
+**JSON is Everywhere:**
+- Web APIS, IoT, logs, configurations
+- Semi-structured, flexible, human-readable
+
+**But Current Solutions Fail:**
+- **Large Databases**: People use MongoDB or PostgreSQL's JSONB to store data
+- **Embeded Databases**: RocksDB and PoloDB lack of ACID and SQL support
+- **Serialization to String**: Or serialize JSON into strings and store in SQLite
 
 
+Serialized JSON with SQL example
 
-## External 1.1
+```sql
+insert into http_request_log (ip, headers)
+values ('127.0.0.1', '{
+    "Content-Type": "application/oct-stream",
+    "X-Forwarded-For": "100.64.0.1",
+}');
+```
 
-Content 1.1
+---
 
-Note: This will only appear in the speaker notes window.
+## Introducing JSONite
+
+**Best of Both Worlds:**
+- SQLite's based
+- Native JSON optimization
+
+**Key Advantages:**
+- ✅ ACID compliance
+- ✅ SQL simplicity  
+- ✅ Serverless C library
+- ✅ Lightning-fast JSON access
+
+---
+
+## Smart Key Optimization
+
+**Key Sorting by Length:**
+```
+{
+  "id": 1,
+  "address": {...}
+  "name": "John",
+  "email": "john@example.com",
+}
+```
+
+**Sorted as:**
+```
+{
+  "id", (2 chars)
+  "name", (4 chars)  
+  "email", (5 chars)
+  "address", (7 chars)
+}
+```
+
+**Binary search on length → Fast lookups**
+
+---
+
+## Handling Massive Data: Smart TOAST
+
+**The Oversized-Attribute Storage Technique**
+- Standard approach: arbitrary chunking
+- JSONite's innovation: **Data-Type Aware TOAST**
+
+**Intelligent Chunking:**
+- Arrays split between elements
+- Objects split between key-value pairs  
+- Text falls back to fixed chunks
+
+**Enables "Slice Detoasting":**
+- `$.logs[1000000:1000010]` fetches only 10 elements
+- Not the entire multi-gigabyte array
 
 
-## External 1.2
+Smart Chunking Example
 
-Content 1.2
+```json
+{
+    "id": 1,
+    "title": "some text",
+    "html": <pointer to TOAST of 200k text>,
+    "photos": [<pointer to TOAST of binary data>],
+    "crawl_logs": [<pointer to TOAST of array of texts>]
+}
+```
 
+---
 
+## Query Power
 
-## External 2
+**Full SQL + JSON Support:**
+- PostgreSQL-compatible JSONB path operators
+- GIN indexes for instant search
 
-Content 2.1
+```sql
+SELECT *
+FROM accounts
+WHERE data @> '{"status": "active"}'
+```
 
+---
 
+## Performance Validation: Benchmark Datasets
 
-## External 3.1
+**Three Specialized Workloads:**
 
-Content 3.1
+1. **YCSB-Style Read Benchmark**
+   - Yahoo! Cloud Serving Benchmark
+   - 1M JSON documents (1KB-100KB each)
 
+2. **TPC-C Inspired Update Benchmark**  
+   - Transaction Processing Performance Council
+   - 100K transactional JSON records
+   - Frequent small field updates
 
-## External 3.2
+3. **Large-Array Slice Benchmark**
+   - Multi-gigabyte JSON documents
+   - Massive arrays (10M+ elements)
 
-Content 3.2
+**Comparison Targets:** SQLite JSONB vs MongoDB vs PostgreSQL vs JSONite
 
+---
 
-## External 3.3 (Image)
+## JSONite: The Future of Embedded Data Storage
 
-![External Image](https://static.slid.es/logo/v2/slides-symbol-512x512.png)
+**Why It Matters Today:**
+- **Edge Computing**: Lightweight, handles sensor data efficiently
+- **Modern Apps**: SQL power + JSON flexibility, no schema migrations
 
+**The Vision:**
+- Open source implementation
+- Community-driven development  
+- Becoming the default choice for embedded JSON storage
+- Bridging SQL reliability with NoSQL flexibility
 
-## External 3.4 (Math)
+---
 
-`\[ J(\theta_0,\theta_1) = \sum_{i=0} \]`
+## Thank You
+
+**Questions?**
+
+*CHEN Yongyuan*  
+*2025-11-01*