use of java.util.Comparator in project hbase by apache.
the class TestThriftHBaseServiceHandler method assertTColumnValuesEqual.
public void assertTColumnValuesEqual(List<TColumnValue> columnValuesA, List<TColumnValue> columnValuesB) {
assertEquals(columnValuesA.size(), columnValuesB.size());
Comparator<TColumnValue> comparator = new Comparator<TColumnValue>() {
@Override
public int compare(TColumnValue o1, TColumnValue o2) {
return Bytes.compareTo(Bytes.add(o1.getFamily(), o1.getQualifier()), Bytes.add(o2.getFamily(), o2.getQualifier()));
}
};
Collections.sort(columnValuesA, comparator);
Collections.sort(columnValuesB, comparator);
for (int i = 0; i < columnValuesA.size(); i++) {
TColumnValue a = columnValuesA.get(i);
TColumnValue b = columnValuesB.get(i);
assertTColumnValueEqual(a, b);
}
}
use of java.util.Comparator in project learning-spark by databricks.
the class Functions method contentSizeStats.
@Nullable
public static final Tuple4<Long, Long, Long, Long> contentSizeStats(JavaRDD<ApacheAccessLog> accessLogRDD) {
JavaDoubleRDD contentSizes = accessLogRDD.mapToDouble(new GetContentSize()).cache();
long count = contentSizes.count();
if (count == 0) {
return null;
}
Object ordering = Ordering.natural();
final Comparator<Double> cmp = (Comparator<Double>) ordering;
return new Tuple4<>(count, contentSizes.reduce(new SumReducer()).longValue(), contentSizes.min(cmp).longValue(), contentSizes.max(cmp).longValue());
}
use of java.util.Comparator in project learning-spark by databricks.
the class LogAnalyzerTotal method processAccessLogs.
public void processAccessLogs(String outDir, JavaDStream<ApacheAccessLog> accessLogsDStream) {
// Calculate statistics based on the content size, and update the static variables to track this.
accessLogsDStream.foreachRDD(new Function<JavaRDD<ApacheAccessLog>, Void>() {
public Void call(JavaRDD<ApacheAccessLog> accessLogs) {
Tuple4<Long, Long, Long, Long> stats = Functions.contentSizeStats(accessLogs);
if (stats != null) {
runningCount.getAndAdd(stats._1());
runningSum.getAndAdd(stats._2());
runningMin.set(Math.min(runningMin.get(), stats._3()));
runningMax.set(Math.max(runningMax.get(), stats._4()));
}
return null;
}
});
// A DStream of Resonse Code Counts;
JavaPairDStream<Integer, Long> responseCodeCountDStream = accessLogsDStream.transformToPair(new Function<JavaRDD<ApacheAccessLog>, JavaPairRDD<Integer, Long>>() {
public JavaPairRDD<Integer, Long> call(JavaRDD<ApacheAccessLog> rdd) {
return Functions.responseCodeCount(rdd);
}
}).updateStateByKey(new Functions.ComputeRunningSum());
responseCodeCountDStream.foreachRDD(new Function<JavaPairRDD<Integer, Long>, Void>() {
public Void call(JavaPairRDD<Integer, Long> rdd) {
currentResponseCodeCounts = rdd.take(100);
return null;
}
});
// A DStream of ipAddressCounts.
JavaPairDStream<String, Long> ipRawDStream = accessLogsDStream.transformToPair(new Function<JavaRDD<ApacheAccessLog>, JavaPairRDD<String, Long>>() {
public JavaPairRDD<String, Long> call(JavaRDD<ApacheAccessLog> rdd) {
return Functions.ipAddressCount(rdd);
}
});
JavaPairDStream<String, Long> ipCumDStream = ipRawDStream.updateStateByKey(new Functions.ComputeRunningSum());
// A DStream of ipAddressCounts without transform
JavaPairDStream<String, Long> ipDStream = accessLogsDStream.mapToPair(new Functions.IpTuple());
JavaPairDStream<String, Long> ipCountsDStream = ipDStream.reduceByKey(new Functions.LongSumReducer());
// and joining it with the transfer amount
JavaPairDStream<String, Long> ipBytesDStream = accessLogsDStream.mapToPair(new Functions.IpContentTuple());
JavaPairDStream<String, Long> ipBytesSumDStream = ipBytesDStream.reduceByKey(new Functions.LongSumReducer());
JavaPairDStream<String, Tuple2<Long, Long>> ipBytesRequestCountDStream = ipBytesSumDStream.join(ipCountsDStream);
// Save our dstream of ip address request counts
JavaPairDStream<Text, LongWritable> writableDStream = ipDStream.mapToPair(new PairFunction<Tuple2<String, Long>, Text, LongWritable>() {
public Tuple2<Text, LongWritable> call(Tuple2<String, Long> e) {
return new Tuple2(new Text(e._1()), new LongWritable(e._2()));
}
});
class OutFormat extends SequenceFileOutputFormat<Text, LongWritable> {
}
;
writableDStream.saveAsHadoopFiles(outDir, "pandas", Text.class, LongWritable.class, OutFormat.class);
// All ips more than 10
JavaDStream<String> ipAddressDStream = ipCumDStream.transform(new Function<JavaPairRDD<String, Long>, JavaRDD<String>>() {
public JavaRDD<String> call(JavaPairRDD<String, Long> rdd) {
return Functions.filterIPAddress(rdd);
}
});
ipAddressDStream.foreachRDD(new Function<JavaRDD<String>, Void>() {
public Void call(JavaRDD<String> rdd) {
List<String> currentIPAddresses = rdd.take(100);
return null;
}
});
// A DStream of endpoint to count.
JavaPairDStream<String, Long> endpointCountsDStream = accessLogsDStream.transformToPair(new Function<JavaRDD<ApacheAccessLog>, JavaPairRDD<String, Long>>() {
public JavaPairRDD<String, Long> call(JavaRDD<ApacheAccessLog> rdd) {
return Functions.endpointCount(rdd);
}
}).updateStateByKey(new Functions.ComputeRunningSum());
Object ordering = Ordering.natural();
final Comparator<Long> cmp = (Comparator<Long>) ordering;
endpointCountsDStream.foreachRDD(new Function<JavaPairRDD<String, Long>, Void>() {
public Void call(JavaPairRDD<String, Long> rdd) {
currentTopEndpoints = rdd.takeOrdered(10, new Functions.ValueComparator<String, Long>(cmp));
return null;
}
});
}
use of java.util.Comparator in project learning-spark by databricks.
the class LogAnalyzerWindowed method processAccessLogs.
public void processAccessLogs(String outDir, JavaDStream<ApacheAccessLog> accessLogsDStream) {
JavaDStream<ApacheAccessLog> windowDStream = accessLogsDStream.window(Flags.getInstance().getWindowLength(), Flags.getInstance().getSlideInterval());
JavaDStream<String> ip = accessLogsDStream.map(new Function<ApacheAccessLog, String>() {
public String call(ApacheAccessLog entry) {
return entry.getIpAddress();
}
});
// reduceByWindow
JavaDStream<Long> requestCountRBW = accessLogsDStream.map(new Function<ApacheAccessLog, Long>() {
public Long call(ApacheAccessLog entry) {
return 1L;
}
}).reduceByWindow(new Function2<Long, Long, Long>() {
public Long call(Long v1, Long v2) {
return v1 + v2;
}
}, new Function2<Long, Long, Long>() {
public Long call(Long v1, Long v2) {
return v1 - v2;
}
}, Flags.getInstance().getWindowLength(), Flags.getInstance().getSlideInterval());
requestCountRBW.print();
// reducebykeyandwindow
JavaPairDStream<String, Long> ipAddressPairDStream = accessLogsDStream.mapToPair(new PairFunction<ApacheAccessLog, String, Long>() {
public Tuple2<String, Long> call(ApacheAccessLog entry) {
return new Tuple2(entry.getIpAddress(), 1L);
}
});
JavaPairDStream<String, Long> ipCountDStream = ipAddressPairDStream.reduceByKeyAndWindow(// Adding elements in the new slice
new Function2<Long, Long, Long>() {
public Long call(Long v1, Long v2) {
return v1 + v2;
}
}, // Removing elements from the oldest slice
new Function2<Long, Long, Long>() {
public Long call(Long v1, Long v2) {
return v1 - v2;
}
}, Flags.getInstance().getWindowLength(), Flags.getInstance().getSlideInterval());
ipCountDStream.print();
// Use countByWindow
JavaDStream<Long> requestCount = accessLogsDStream.countByWindow(Flags.getInstance().getWindowLength(), Flags.getInstance().getSlideInterval());
JavaPairDStream<String, Long> ipAddressRequestCount = ip.countByValueAndWindow(Flags.getInstance().getWindowLength(), Flags.getInstance().getSlideInterval());
requestCount.print();
ipAddressRequestCount.print();
// use a transform for the response code count
JavaPairDStream<Integer, Long> responseCodeCountTransform = accessLogsDStream.transformToPair(new Function<JavaRDD<ApacheAccessLog>, JavaPairRDD<Integer, Long>>() {
public JavaPairRDD<Integer, Long> call(JavaRDD<ApacheAccessLog> logs) {
return Functions.responseCodeCount(logs);
}
});
windowDStream.foreachRDD(new Function<JavaRDD<ApacheAccessLog>, Void>() {
public Void call(JavaRDD<ApacheAccessLog> accessLogs) {
Tuple4<Long, Long, Long, Long> contentSizeStats = Functions.contentSizeStats(accessLogs);
List<Tuple2<Integer, Long>> responseCodeToCount = Functions.responseCodeCount(accessLogs).take(100);
JavaPairRDD<String, Long> ipAddressCounts = Functions.ipAddressCount(accessLogs);
List<String> ip = Functions.filterIPAddress(ipAddressCounts).take(100);
Object ordering = Ordering.natural();
Comparator<Long> cmp = (Comparator<Long>) ordering;
List<Tuple2<String, Long>> topEndpoints = Functions.endpointCount(accessLogs).top(10, new Functions.ValueComparator<String, Long>(cmp));
logStatistics = new LogStatistics(contentSizeStats, responseCodeToCount, ip, topEndpoints);
return null;
}
});
}
use of java.util.Comparator in project druid by druid-io.
the class CountAggregatorTest method testComparator.
@Test
public void testComparator() {
CountAggregator agg = new CountAggregator();
Object first = agg.get();
agg.aggregate();
Comparator comp = new CountAggregatorFactory("null").getComparator();
Assert.assertEquals(-1, comp.compare(first, agg.get()));
Assert.assertEquals(0, comp.compare(first, first));
Assert.assertEquals(0, comp.compare(agg.get(), agg.get()));
Assert.assertEquals(1, comp.compare(agg.get(), first));
}
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