kaori-seasons commented on PR #1923:
URL: https://github.com/apache/fluss/pull/1923#issuecomment-3509321526
These are some advantages of adaptive strategies:
### 1. Finer Control and Optimization
Our approach provides smarter read strategies through
`FlussUnionReadManager`:
```java
public enum UnionReadStrategy {
REAL_TIME_ONLY, // Read real-time data only
HISTORICAL_ONLY, // Read historical data only
UNION, // Union read
ADAPTIVE // Adaptive strategy
}
```
This strategy can dynamically select the optimal read approach based on
query characteristics, rather than simply combining two data sources.
### 2. Intelligent Analysis and Adaptive Optimization
Our implementation includes complex analysis logic that can perform adaptive
optimization based on historical performance data:
```java
// Analyze query characteristics to determine optimal strategy
private StrategyAnalysisResult performStrategyAnalysis(FlussTableHandle
tableHandle) {
// 1. Limit analysis
double limitBenefit = analyzeLimitBenefit(tableHandle);
// 2. Predicate analysis
PredicateAnalysisResult predicateAnalysis =
analyzePredicates(tableHandle);
// 3. Column projection analysis
double projectionBenefit = analyzeProjectionBenefit(tableHandle);
// 4. Time boundary analysis
TimeBoundaryAnalysis timeAnalysis = analyzeTimeBoundary(tableHandle);
// 5. Data freshness analysis
double freshnessBenefit = analyzeDataFreshness(tableHandle);
// Calculate overall benefits
double realTimeBenefit = calculateRealTimeBenefit(
limitBenefit, predicateAnalysis, projectionBenefit,
freshnessBenefit);
double historicalBenefit = calculateHistoricalBenefit(
limitBenefit, predicateAnalysis, projectionBenefit,
timeAnalysis);
return new StrategyAnalysisResult(
realTimeBenefit,
historicalBenefit,
// ... other parameters
);
}
```
### 3. Avoiding Data Duplication and Consistency Issues
Through custom implementation, we can ensure that data duplication is
avoided during union reads and handle consistency issues between real-time and
historical data:
```java
// Check time boundaries to avoid data duplication
private TimeBoundaryAnalysis analyzeTimeBoundary(FlussTableHandle
tableHandle) {
Optional<Long> syncBoundary = getLakehouseSyncTimeBoundary(tableHandle);
if (syncBoundary.isPresent()) {
// Ensure real-time reads don't include data already synced to
Lakehouse
// Ensure historical reads don't include unsynced real-time data
return new TimeBoundaryAnalysis(syncBoundary.get(), true);
}
return new TimeBoundaryAnalysis(0L, false);
}
```
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