Given a String expression composed of visits / time like : "1/24h,1..3/3h,5/*"
Then the result should be the following list of Strings
"1/24h",
"1/3h","2/3h","3/3h",
"5/1h","5/2h","5/3h","5/4h","5/5h",until ,"24/1h"
So, 2 things need to be solved, the dots and the stars for the visits and for the time.
I will use Java 8 , but I'll show you the difference between implementing this logic using Functional and implementing it in a traditional way with loops and ifs.
package com.marco;
import java.util.ArrayList;
import java.util.List;
import java.util.function.Function;
import java.util.stream.Collectors;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.Lists;
public class ExpressionConverter {
private static final String COMMA = ",";
private static final String SEPARATOR = "/";
private final ImmutableList<Function<String, List<String>>> visitFunctions;
private final ImmutableList<Function<String, List<String>>> timeFunctions;
public ExpressionConverter(DotsVisitFunction dotsVisitFunction, StarVisitFunction starVisitFunction, StandardFunction standardFunction,
StarTimeFunction starTimeFunction) {
this.visitFunctions = ImmutableList.of(dotsVisitFunction, starVisitFunction, standardFunction);
this.timeFunctions = ImmutableList.of(starTimeFunction, standardFunction);
}
public List<String> convertVisitTimeExpressionFunctional(String visitTimeExpression) {
return Lists.newArrayList(visitTimeExpression.split(COMMA)).parallelStream().filter(it -> !it.isEmpty())
.map(it -> interpretSingleExpressionFunctional(it)).flatMap(it -> it.parallelStream()).collect(Collectors.toList());
}
public List<String> convertVisitTimeExpressionTraditional(String visitTimeExpression) {
List<String> result = new ArrayList<String>();
for (String singleVisitTime : visitTimeExpression.split(COMMA)) {
if (!singleVisitTime.isEmpty()) {
result.addAll(interpretSingleVisitTimeExpressionTraditional(singleVisitTime));
}
}
return result;
}
private List<String> interpretSingleExpressionFunctional(String singleExpression) {
String visit = singleExpression.split(SEPARATOR)[0];
String time = singleExpression.split(SEPARATOR)[1];
List<String> result = Lists.newArrayList();
visitFunctions.stream().map(it -> it.apply(visit)).flatMap(it -> it.stream()).forEach(visitIt -> {
timeFunctions.stream().map(it -> it.apply(time)).flatMap(it -> it.stream()).forEach(timeIt -> {
result.add(visitIt + SEPARATOR + timeIt);
});
});
return result;
}
private List<String> interpretSingleVisitTimeExpressionTraditional(String singleExpression) {
String visit = singleExpression.split(SEPARATOR)[0];
String time = singleExpression.split(SEPARATOR)[1];
List<String> result = Lists.newArrayList();
List<String> visists = Lists.newArrayList();
List<String> times = Lists.newArrayList();
for (Function<String, List<String>> visitFunction : visitFunctions) {
visists.addAll(visitFunction.apply(visit));
}
for (Function<String, List<String>> timeFunction : timeFunctions) {
times.addAll(timeFunction.apply(time));
}
for (String visitIt : visists) {
for (String timeIt : times) {
result.add(visitIt + SEPARATOR + timeIt);
}
}
return result;
}
}
As you can see we have 2 public and 2 private methods, functional and traditional.
Here is a simple test focusing on the performance of the two styles :
package com.marco; import static org.mockito.Matchers.any; import static org.mockito.Matchers.anyInt; import static org.mockito.Matchers.anyLong; import static org.mockito.Mockito.mock; import static org.mockito.Mockito.when; import java.math.BigDecimal; import java.util.Set; import org.junit.Before; import org.junit.Test; import com.google.common.collect.ImmutableSet; import com.google.common.collect.Sets; public class ExpressionConverterTest { private static final String EXPRESSIONS = 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private Cache cache; private ExpressionConverter expressionConverter; @Before public void init() { cache = mock(Cache.class); expressionConverter = new ExpressionConverter(new DotsVisitFunction(cache), new StarVisitFunction(cache), new StandardFunction(), new StarTimeFunction(cache)); Set<Integer> totVisists = Sets.newHashSet(); for (int i = 1; i <= 100; i++) { totVisists.add(i); } when(cache.getVisits(anyLong(), (BigDecimal) any(), anyInt())).thenReturn(ImmutableSet.copyOf(totVisists)); } @Test public void testPerf() { long averageTraditional = 0l; long averageFuntional = 0l; for (int a = 0; a < 10; a++) { long start = System.currentTimeMillis(); for (int i = 0; i < 1000; i++) { expressionConverter.convertVisitTimeExpressionTraditional(EXPRESSIONS); } System.out.println("Traditional java " + (System.currentTimeMillis() - start) + " ms"); averageTraditional += (System.currentTimeMillis() - start); long start2 = System.currentTimeMillis(); for (int i = 0; i < 1000; i++) { expressionConverter.convertVisitTimeExpressionFunctional(EXPRESSIONS); } System.out.println("Functional java " + (System.currentTimeMillis() - start2) + " ms"); averageFuntional += (System.currentTimeMillis() - start2); } System.out.println("Average Traditional java : " + (averageTraditional / 10) + " ms"); System.out.println("Average Functional java : " + (averageFuntional / 10) + " ms"); } }
And this is the output :Traditional java 1274 ms
Functional java 773 ms
Traditional java 1054 ms
Functional java 531 ms
Traditional java 961 ms
Functional java 493 ms
Traditional java 948 ms
Functional java 492 ms
Traditional java 949 ms
Functional java 491 ms
Traditional java 958 ms
Functional java 481 ms
Traditional java 1004 ms
Functional java 474 ms
Traditional java 949 ms
Functional java 471 ms
Traditional java 947 ms
Functional java 475 ms
Traditional java 942 ms
Functional java 472 ms
Average Traditional java : 998 ms
Average Functional java : 515 ms
Functional is 2 times faster than Traditional. Why?
Because of this : parallelStream()
Parallel Stream will split the job in several tasks leveraging your multicore system.
So can you put parallelStream() everywhere and replace all the stream() methods with parallelStream() ??
No!
The parallelStream()can in fact cause a big degradation of performance if used in the wrong place.
There are loads of posts out there on this argument that should be read before using this feature, but just remember, if you want to use parallelStream() make sure to measure the performance before and after!!!!!!!!!!
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