feat: Add GaussDB CDC connector with critical bug fixes

README.md

@@ -112,10 +112,16 @@ SELECT * FROM test_table;
  ```
 5. View job execution status through Flink WebUI or downstream database.
 
+- **GaussDB**: Supports full snapshot and incremental CDC for Huawei GaussDB using `mppdb_decoding`.
+- **MySQL**: Supports full snapshot and incremental CDC for MySQL.
+- ... (others)
+
 Try it out yourself with our more detailed [tutorial](docs/content/docs/get-started/quickstart/mysql-to-doris.md). 
 You can also see [connector overview](docs/content/docs/connectors/pipeline-connectors/overview.md) to view a comprehensive catalog of the
 connectors currently provided and understand more detailed configurations.
 
+For GaussDB specific integration, see the [GaussDB Connector Guide](flink-cdc-connect/flink-cdc-source-connectors/flink-connector-gaussdb-cdc/README.md).
+
 ### Join the Community
 
 There are many ways to participate in the Apache Flink CDC community. The

README_TEST.md

@@ -0,0 +1,189 @@
+# GaussDB CDC 一键测试
+
+## 🚀 快速开始
+
+```bash
+./test_gaussdb_cdc.sh
+```
+
+就这么简单！脚本会自动完成：
+1. ✅ 部署最新代码
+2. ✅ 运行完整测试
+3. ✅ 验证数据一致性
+
+---
+
+## 📋 测试流程
+
+该脚本按顺序执行以下步骤：
+
+### 步骤 1: 部署最新代码
+- 强制清理 Maven 缓存
+- 编译最新代码
+- 部署到 Flink 集群
+- 重启集群并提交作业
+
+### 步骤 2: 运行增量同步测试
+- 初始化测试环境
+- 测试 INSERT 操作
+- 测试 UPDATE 操作
+- 测试 DELETE 操作
+- 验证每个操作的同步结果
+
+### 步骤 3: 验证数据一致性
+- 比较 GaussDB 和 MySQL 记录数量
+- 比较数据内容完整性
+- 验证测试数据同步状态
+
+---
+
+## 📊 输出示例
+
+### 成功时：
+```
+╔══════════════════════════════════════════════════════════════════╗
+║                      测试完成报告                                ║
+╚══════════════════════════════════════════════════════════════════╝
+
+测试结果:
+  ✅ 步骤 1: 部署成功
+  ✅ 步骤 2: 测试通过 (INSERT/UPDATE/DELETE)
+  ✅ 步骤 3: 数据一致性验证通过
+
+测试统计:
+  ⏱️  总耗时: 2 分 30 秒
+  📅 完成时间: 2025-12-23 18:15:00
+
+╔══════════════════════════════════════════════════════════════════╗
+║  🎉 恭喜！所有测试通过！                                         ║
+║  GaussDB CDC 增量同步功能正常工作                                ║
+╚══════════════════════════════════════════════════════════════════╝
+```
+
+### 失败时：
+```
+╔══════════════════════════════════════════════════════════════════╗
+║  ❌ 测试失败                                                     ║
+╚══════════════════════════════════════════════════════════════════╝
+
+💡 故障排查建议:
+  1. 查看 Flink 日志: docker logs flink-taskmanager
+  2. 检查作业状态: docker exec flink-jobmanager ./bin/flink list
+  3. 验证数据库连接: ./run_gaussdb_test.sh init
+  4. 查看详细文档: cat TEST_SCRIPTS_GUIDE.md
+```
+
+---
+
+## 🔧 单独运行各个步骤
+
+如果需要单独运行某个步骤：
+
+```bash
+# 只部署
+./deploy_gaussdb.sh
+
+# 只测试
+./run_gaussdb_test.sh test
+
+# 只验证
+./check_sync_result.sh
+```
+
+---
+
+## 📖 详细文档
+
+查看完整的使用指南：
+```bash
+cat TEST_SCRIPTS_GUIDE.md
+```
+
+---
+
+## 🎯 返回值
+
+- `0` - 所有测试通过
+- `1` - 测试失败
+
+可用于 CI/CD 流程：
+```bash
+if ./test_gaussdb_cdc.sh; then
+    echo "部署到生产环境"
+else
+    echo "测试失败，停止部署"
+    exit 1
+fi
+```
+
+---
+
+## 📞 故障排查
+
+### 常见问题
+
+**Q: 部署失败怎么办？**
+```bash
+# 检查 Maven 构建日志
+mvn clean install -DskipTests
+
+# 检查 Docker 容器状态
+docker ps
+```
+
+**Q: 测试失败怎么办？**
+```bash
+# 查看 Flink 日志
+docker logs flink-taskmanager | tail -100
+
+# 检查数据库连接
+./run_gaussdb_test.sh init
+```
+
+**Q: 验证失败怎么办？**
+```bash
+# 手动检查数据
+./check_sync_result.sh
+
+# 清理测试数据重试
+./run_gaussdb_test.sh cleanup
+./test_gaussdb_cdc.sh
+```
+
+---
+
+## 🔄 持续集成示例
+
+```yaml
+# .github/workflows/test.yml
+name: GaussDB CDC Test
+
+on: [push, pull_request]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Run CDC Test
+        run: ./test_gaussdb_cdc.sh
+```
+
+---
+
+## 📝 版本信息
+
+- **版本**: 2.0
+- **更新日期**: 2025-12-23
+- **维护者**: GaussDB CDC Team
+
+---
+
+## 🎉 快速验证
+
+修改代码后，只需运行：
+```bash
+./test_gaussdb_cdc.sh
+```
+
+就能完整验证 CDC 功能是否正常！

check_distributed_sync_result.sh

@@ -0,0 +1,128 @@
+#!/bin/bash
+
+# ==============================================================================
+# GaussDB Distributed CDC Sync Result Verification Script
+# 验证多个 GaussDB DN 和 MySQL 之间的数据一致性
+# ==============================================================================
+
+set -e
+
+# 颜色定义
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+CYAN='\033[0;36m'
+NC='\033[0m' # No Color
+
+# DN Connection Details
+DN_HOSTS=("10.250.0.30" "10.250.0.181" "10.250.0.157")
+DN_PORTS=("40000" "40020" "40040")
+DB_USER="tom"
+DB_PASS="Gauss_235"
+DB_NAME="db1"
+
+# CN Connection Details
+CN_HOST="10.250.0.51"
+CN_PORT="8000"
+
+# 测试数据ID
+TEST_ID_BASE=900
+
+echo -e "${BLUE}╔════════════════════════════════════════════════════════════╗${NC}"
+echo -e "${BLUE}║  GaussDB Distributed CDC 同步结果验证                      ║${NC}"
+echo -e "${BLUE}╚════════════════════════════════════════════════════════════╝${NC}"
+echo ""
+
+# ========== 1. 获取所有 GaussDB DN 的汇总数据 ==========
+echo -e "${CYAN}📊 Fetching data from all GaussDB DNs...${NC}"
+GAUSSDB_TOTAL_DATA=""
+GAUSSDB_TOTAL_COUNT=0
+
+for i in "${!DN_HOSTS[@]}"; do
+    host=${DN_HOSTS[$i]}
+    port=${DN_PORTS[$i]}
+    echo -ne "  -> DN$((i+1)) ($host:$port)... "
+    DN_DATA=$(PGPASSWORD=$DB_PASS psql -h $host -p $port -U $DB_USER -d $DB_NAME -t -A -F'|' -c "SELECT product_id, product_name, category, price, stock FROM products;" 2>/dev/null || true)
+    DN_COUNT=$(echo "$DN_DATA" | grep -v '^$' | wc -l | tr -d ' ')
+    echo -e "${GREEN}$DN_COUNT records${NC}"
+
+    if [ -n "$DN_DATA" ]; then
+        if [ -n "$GAUSSDB_TOTAL_DATA" ]; then
+            GAUSSDB_TOTAL_DATA="${GAUSSDB_TOTAL_DATA}\n${DN_DATA}"
+        else
+            GAUSSDB_TOTAL_DATA="$DN_DATA"
+        fi
+    fi
+    GAUSSDB_TOTAL_COUNT=$((GAUSSDB_TOTAL_COUNT + DN_COUNT))
+done
+
+echo -e "  Total records in GaussDB (all DNs): ${GREEN}$GAUSSDB_TOTAL_COUNT${NC}"
+
+# ========== 2. 获取 MySQL 数据 ==========
+echo -e "${CYAN}📊 Fetching data from MySQL...${NC}"
+MYSQL_DATA=$(docker exec mysql-sink mysql -uflinkuser -pflinkpw inventory --default-character-set=utf8mb4 -se "SELECT product_id, product_name, category, price, stock FROM products_sink ORDER BY product_id;" 2>/dev/null | tr '\t' '|')
+MYSQL_COUNT=$(echo "$MYSQL_DATA" | grep -v '^$' | wc -l | tr -d ' ')
+
+echo -e "  Total records in MySQL: ${GREEN}$MYSQL_COUNT${NC}"
+echo ""
+
+# ========== 3. 比较记录数量 ==========
+echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${BLUE}📈 Record Count Comparison${NC}"
+echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+
+if [ "$GAUSSDB_TOTAL_COUNT" -eq "$MYSQL_COUNT" ]; then
+    echo -e "${GREEN}✅ Record count matches: $GAUSSDB_TOTAL_COUNT records${NC}"
+    COUNT_MATCH=true
+else
+    echo -e "${RED}❌ Record count mismatch!${NC}"
+    echo -e "   GaussDB (Total): $GAUSSDB_TOTAL_COUNT records"
+    echo -e "   MySQL:           $MYSQL_COUNT records"
+    echo -e "   Diff:            $((GAUSSDB_TOTAL_COUNT - MYSQL_COUNT)) records"
+    COUNT_MATCH=false
+fi
+echo ""
+
+# ========== 4. 比较数据内容 ==========
+echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${BLUE}🔍 Data Content Comparison${NC}"
+echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+
+# 排序并比较数据
+GAUSSDB_SORTED=$(echo -e "$GAUSSDB_TOTAL_DATA" | grep -v '^$' | sort)
+MYSQL_SORTED=$(echo "$MYSQL_DATA" | grep -v '^$' | sort)
+
+if [ "$GAUSSDB_SORTED" == "$MYSQL_SORTED" ]; then
+    echo -e "${GREEN}✅ Data content matches perfectly!${NC}"
+    CONTENT_MATCH=true
+else
+    echo -e "${RED}❌ Data content mismatch detected!${NC}"
+    echo ""
+    echo -e "${YELLOW}Differences:${NC}"
+
+    # 显示差异
+    diff <(echo "$GAUSSDB_SORTED") <(echo "$MYSQL_SORTED") | head -20 || true
+
+    CONTENT_MATCH=false
+fi
+echo ""
+
+# ========== 5. 最终结果 ==========
+echo -e "${BLUE}╔════════════════════════════════════════════════════════════╗${NC}"
+echo -e "${BLUE}║  验证结果总结                                              ║${NC}"
+echo -e "${BLUE}╚════════════════════════════════════════════════════════════╝${NC}"
+
+if [ "$COUNT_MATCH" = true ] && [ "$CONTENT_MATCH" = true ]; then
+    echo -e "${GREEN}✅ Record Count:  PASSED${NC}"
+    echo -e "${GREEN}✅ Data Content:  PASSED${NC}"
+    echo ""
+    echo -e "${GREEN}🎉 All checks PASSED! Distributed CDC sync is working correctly.${NC}"
+    exit 0
+else
+    [ "$COUNT_MATCH" = true ] && echo -e "${GREEN}✅ Record Count:  PASSED${NC}" || echo -e "${RED}❌ Record Count:  FAILED${NC}"
+    [ "$CONTENT_MATCH" = true ] && echo -e "${GREEN}✅ Data Content:  PASSED${NC}" || echo -e "${RED}❌ Data Content:  FAILED${NC}"
+    echo ""
+    echo -e "${RED}❌ Some checks FAILED. Distributed CDC sync may have issues.${NC}"
+    exit 1
+fi