Example usage for org.joda.time Instant minus

Introduction

In this page you can find the example usage for org.joda.time Instant minus.

Prototype

public Instant minus(ReadableDuration duration) 

Source Link

Document

Gets a copy of this instant with the specified duration taken away.

Usage

From source file:com.auth10.federation.SamlTokenValidator.java

License:Open Source License

private boolean validateExpiration(Instant notBefore, Instant notOnOrAfter) {

    Instant now = new Instant();
    Duration skew = new Duration(MAX_CLOCK_SKEW_IN_MINUTES * 60 * 1000);

    if (now.plus(skew).isBefore(notBefore)) {
        return true;
    }//  w  w w  .  jav a 2  s.  co  m

    if (now.minus(skew).isAfter(notOnOrAfter)) {
        return true;
    }

    return false;
}

---

From source file:com.example.geomesa.kafka.KafkaQuickStart.java

License:Open Source License

public static void main(String[] args) throws Exception {
    // read command line args for a connection to Kafka
    CommandLineParser parser = new BasicParser();
    Options options = getCommonRequiredOptions();
    CommandLine cmd = parser.parse(options, args);

    // create the producer and consumer KafkaDataStore objects
    Map<String, String> dsConf = getKafkaDataStoreConf(cmd);
    dsConf.put("isProducer", "true");
    DataStore producerDS = DataStoreFinder.getDataStore(dsConf);
    dsConf.put("isProducer", "false");
    DataStore consumerDS = DataStoreFinder.getDataStore(dsConf);

    // verify that we got back our KafkaDataStore objects properly
    if (producerDS == null) {
        throw new Exception("Null producer KafkaDataStore");
    }/*w w  w. ja v a2  s  . c  o m*/
    if (consumerDS == null) {
        throw new Exception("Null consumer KafkaDataStore");
    }

    // create the schema which creates a topic in Kafka
    // (only needs to be done once)
    final String sftName = "KafkaQuickStart";
    final String sftSchema = "name:String,age:Int,dtg:Date,*geom:Point:srid=4326";
    SimpleFeatureType sft = SimpleFeatureTypes.createType(sftName, sftSchema);
    // set zkPath to default if not specified
    String zkPath = (dsConf.get(ZK_PATH) == null) ? "/geomesa/ds/kafka" : dsConf.get(ZK_PATH);
    SimpleFeatureType preppedOutputSft = KafkaDataStoreHelper.createStreamingSFT(sft, zkPath);
    // only create the schema if it hasn't been created already
    if (!Arrays.asList(producerDS.getTypeNames()).contains(sftName))
        producerDS.createSchema(preppedOutputSft);

    System.out.println("Register KafkaDataStore in GeoServer (Press enter to continue)");
    System.in.read();

    // the live consumer must be created before the producer writes features
    // in order to read streaming data.
    // i.e. the live consumer will only read data written after its instantiation
    SimpleFeatureSource consumerFS = consumerDS.getFeatureSource(sftName);
    SimpleFeatureStore producerFS = (SimpleFeatureStore) producerDS.getFeatureSource(sftName);

    // creates and adds SimpleFeatures to the producer every 1/5th of a second
    System.out.println("Writing features to Kafka... refresh GeoServer layer preview to see changes");
    Instant replayStart = new Instant();
    addSimpleFeatures(sft, producerFS);
    Instant replayEnd = new Instant();

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    SimpleFeatureCollection featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    addDeleteNewFeature(sft, producerFS);

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    // the state of the two SimpleFeatures is real time here
    System.out.println("Here are the two SimpleFeatures that were obtained with the live consumer:");
    SimpleFeatureIterator featureIterator = featureCollection.features();
    SimpleFeature feature1 = featureIterator.next();
    SimpleFeature feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    // REPLAY CONSUMER - will obtain the state of SimpleFeatures at any specified time
    // Replay consumer requires a ReplayConfig which takes a time range and a
    // duration of time to process
    System.out.println("\nConsuming with the replay consumer...");
    Duration readBehind = new Duration(1000); // 1 second readBehind
    ReplayConfig rc = new ReplayConfig(replayStart, replayEnd, readBehind);
    SimpleFeatureType replaySFT = KafkaDataStoreHelper.createReplaySFT(preppedOutputSft, rc);
    producerDS.createSchema(replaySFT);
    SimpleFeatureSource replayConsumerFS = consumerDS.getFeatureSource(replaySFT.getName());

    // querying for the state of SimpleFeatures approximately 5 seconds before the replayEnd.
    // the ReplayKafkaConsumerFeatureSource will build the state of SimpleFeatures
    // by processing all of the messages that were sent in between queryTime-readBehind and queryTime.
    // only the messages in between replayStart and replayEnd are cached.
    Instant queryTime = replayEnd.minus(5000);
    featureCollection = replayConsumerFS.getFeatures(ReplayTimeHelper.toFilter(queryTime));
    System.out.println(featureCollection.size() + " features were written to Kafka");

    System.out.println("Here are the two SimpleFeatures that were obtained with the replay consumer:");
    featureIterator = featureCollection.features();
    feature1 = featureIterator.next();
    feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    if (System.getProperty("clear") != null) {
        // Run Java command with -Dclear=true
        // This will cause a 'clear'
        producerFS.removeFeatures(Filter.INCLUDE);
    }

    System.exit(0);
}

---

From source file:com.example.geomesa.kafka08.KafkaQuickStart.java

License:Open Source License

public static void main(String[] args) throws Exception {
    // read command line args for a connection to Kafka
    CommandLineParser parser = new BasicParser();
    Options options = getCommonRequiredOptions();
    CommandLine cmd = parser.parse(options, args);

    // create the producer and consumer KafkaDataStore objects
    Map<String, String> dsConf = getKafkaDataStoreConf(cmd);
    dsConf.put("isProducer", "true");
    DataStore producerDS = DataStoreFinder.getDataStore(dsConf);
    dsConf.put("isProducer", "false");
    DataStore consumerDS = DataStoreFinder.getDataStore(dsConf);

    // verify that we got back our KafkaDataStore objects properly
    if (producerDS == null) {
        throw new Exception("Null producer KafkaDataStore");
    }/*w  w  w.  j ava 2s.  c  o m*/
    if (consumerDS == null) {
        throw new Exception("Null consumer KafkaDataStore");
    }

    // create the schema which creates a topic in Kafka
    // (only needs to be done once)
    final String sftName = "KafkaQuickStart08";
    final String sftSchema = "name:String,age:Int,dtg:Date,*geom:Point:srid=4326";
    SimpleFeatureType sft = SimpleFeatureTypes.createType(sftName, sftSchema);
    // set zkPath to default if not specified
    String zkPath = (dsConf.get(ZK_PATH) == null) ? "/geomesa/ds/kafka" : dsConf.get(ZK_PATH);
    SimpleFeatureType preppedOutputSft = KafkaDataStoreHelper.createStreamingSFT(sft, zkPath);
    // only create the schema if it hasn't been created already
    if (!Arrays.asList(producerDS.getTypeNames()).contains(sftName))
        producerDS.createSchema(preppedOutputSft);
    if (!cmd.hasOption("automated")) {
        System.out.println("Register KafkaDataStore in GeoServer (Press enter to continue)");
        System.in.read();
    }

    // the live consumer must be created before the producer writes features
    // in order to read streaming data.
    // i.e. the live consumer will only read data written after its instantiation
    SimpleFeatureSource consumerFS = consumerDS.getFeatureSource(sftName);
    SimpleFeatureStore producerFS = (SimpleFeatureStore) producerDS.getFeatureSource(sftName);

    // creates and adds SimpleFeatures to the producer every 1/5th of a second
    System.out.println("Writing features to Kafka... refresh GeoServer layer preview to see changes");
    Instant replayStart = new Instant();

    String vis = cmd.getOptionValue(VISIBILITY);
    if (vis != null)
        System.out.println("Writing features with " + vis);
    addSimpleFeatures(sft, producerFS, vis);
    Instant replayEnd = new Instant();

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    SimpleFeatureCollection featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    addDeleteNewFeature(sft, producerFS);

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    // the state of the two SimpleFeatures is real time here
    System.out.println("Here are the two SimpleFeatures that were obtained with the live consumer:");
    SimpleFeatureIterator featureIterator = featureCollection.features();
    SimpleFeature feature1 = featureIterator.next();
    SimpleFeature feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    // REPLAY CONSUMER - will obtain the state of SimpleFeatures at any specified time
    // Replay consumer requires a ReplayConfig which takes a time range and a
    // duration of time to process
    System.out.println("\nConsuming with the replay consumer...");
    Duration readBehind = new Duration(1000); // 1 second readBehind
    ReplayConfig rc = new ReplayConfig(replayStart, replayEnd, readBehind);
    SimpleFeatureType replaySFT = KafkaDataStoreHelper.createReplaySFT(preppedOutputSft, rc);
    producerDS.createSchema(replaySFT);
    SimpleFeatureSource replayConsumerFS = consumerDS.getFeatureSource(replaySFT.getName());

    // querying for the state of SimpleFeatures approximately 5 seconds before the replayEnd.
    // the ReplayKafkaConsumerFeatureSource will build the state of SimpleFeatures
    // by processing all of the messages that were sent in between queryTime-readBehind and queryTime.
    // only the messages in between replayStart and replayEnd are cached.
    Instant queryTime = replayEnd.minus(5000);
    featureCollection = replayConsumerFS.getFeatures(ReplayTimeHelper.toFilter(queryTime));
    System.out.println(featureCollection.size() + " features were written to Kafka");

    System.out.println("Here are the two SimpleFeatures that were obtained with the replay consumer:");
    featureIterator = featureCollection.features();
    feature1 = featureIterator.next();
    feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    if (System.getProperty("clear") != null) {
        // Run Java command with -Dclear=true
        // This will cause a 'clear'
        producerFS.removeFeatures(Filter.INCLUDE);
    }

    System.exit(0);
}

---

From source file:com.example.geomesa.kafka09.KafkaQuickStart.java

License:Open Source License

public static void main(String[] args) throws Exception {
    // read command line args for a connection to Kafka
    CommandLineParser parser = new BasicParser();
    Options options = getCommonRequiredOptions();
    CommandLine cmd = parser.parse(options, args);

    // create the producer and consumer KafkaDataStore objects
    Map<String, String> dsConf = getKafkaDataStoreConf(cmd);
    dsConf.put("isProducer", "true");
    DataStore producerDS = DataStoreFinder.getDataStore(dsConf);
    dsConf.put("isProducer", "false");
    DataStore consumerDS = DataStoreFinder.getDataStore(dsConf);

    // verify that we got back our KafkaDataStore objects properly
    if (producerDS == null) {
        throw new Exception("Null producer KafkaDataStore");
    }//w  ww . ja v  a 2  s.  c  o  m
    if (consumerDS == null) {
        throw new Exception("Null consumer KafkaDataStore");
    }

    // create the schema which creates a topic in Kafka
    // (only needs to be done once)
    final String sftName = "KafkaQuickStart09";
    final String sftSchema = "name:String,age:Int,dtg:Date,*geom:Point:srid=4326";
    SimpleFeatureType sft = SimpleFeatureTypes.createType(sftName, sftSchema);
    // set zkPath to default if not specified
    String zkPath = (dsConf.get(ZK_PATH) == null) ? "/geomesa/ds/kafka" : dsConf.get(ZK_PATH);
    SimpleFeatureType preppedOutputSft = KafkaDataStoreHelper.createStreamingSFT(sft, zkPath);
    // only create the schema if it hasn't been created already
    if (!Arrays.asList(producerDS.getTypeNames()).contains(sftName))
        producerDS.createSchema(preppedOutputSft);
    if (!cmd.hasOption("automated")) {
        System.out.println("Register KafkaDataStore in GeoServer (Press enter to continue)");
        System.in.read();
    }

    // the live consumer must be created before the producer writes features
    // in order to read streaming data.
    // i.e. the live consumer will only read data written after its instantiation
    SimpleFeatureSource consumerFS = consumerDS.getFeatureSource(sftName);
    SimpleFeatureStore producerFS = (SimpleFeatureStore) producerDS.getFeatureSource(sftName);

    // creates and adds SimpleFeatures to the producer every 1/5th of a second
    System.out.println("Writing features to Kafka... refresh GeoServer layer preview to see changes");
    Instant replayStart = new Instant();

    String vis = cmd.getOptionValue(VISIBILITY);
    if (vis != null)
        System.out.println("Writing features with " + vis);
    addSimpleFeatures(sft, producerFS, vis);
    Instant replayEnd = new Instant();

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    SimpleFeatureCollection featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    addDeleteNewFeature(sft, producerFS);

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    // the state of the two SimpleFeatures is real time here
    System.out.println("Here are the two SimpleFeatures that were obtained with the live consumer:");
    SimpleFeatureIterator featureIterator = featureCollection.features();
    SimpleFeature feature1 = featureIterator.next();
    SimpleFeature feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    // REPLAY CONSUMER - will obtain the state of SimpleFeatures at any specified time
    // Replay consumer requires a ReplayConfig which takes a time range and a
    // duration of time to process
    System.out.println("\nConsuming with the replay consumer...");
    Duration readBehind = new Duration(1000); // 1 second readBehind
    ReplayConfig rc = new ReplayConfig(replayStart, replayEnd, readBehind);
    SimpleFeatureType replaySFT = KafkaDataStoreHelper.createReplaySFT(preppedOutputSft, rc);
    producerDS.createSchema(replaySFT);
    SimpleFeatureSource replayConsumerFS = consumerDS.getFeatureSource(replaySFT.getName());

    // querying for the state of SimpleFeatures approximately 5 seconds before the replayEnd.
    // the ReplayKafkaConsumerFeatureSource will build the state of SimpleFeatures
    // by processing all of the messages that were sent in between queryTime-readBehind and queryTime.
    // only the messages in between replayStart and replayEnd are cached.
    Instant queryTime = replayEnd.minus(5000);
    featureCollection = replayConsumerFS.getFeatures(ReplayTimeHelper.toFilter(queryTime));
    System.out.println(featureCollection.size() + " features were written to Kafka");

    System.out.println("Here are the two SimpleFeatures that were obtained with the replay consumer:");
    featureIterator = featureCollection.features();
    feature1 = featureIterator.next();
    feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    if (System.getProperty("clear") != null) {
        // Run Java command with -Dclear=true
        // This will cause a 'clear'
        producerFS.removeFeatures(Filter.INCLUDE);
    }

    System.exit(0);
}

---

From source file:com.example.geomesa.kafka10.KafkaQuickStart.java

License:Open Source License

public static void main(String[] args) throws Exception {
    // read command line args for a connection to Kafka
    CommandLineParser parser = new BasicParser();
    Options options = getCommonRequiredOptions();
    CommandLine cmd = parser.parse(options, args);

    // create the producer and consumer KafkaDataStore objects
    Map<String, String> dsConf = getKafkaDataStoreConf(cmd);
    dsConf.put("isProducer", "true");
    DataStore producerDS = DataStoreFinder.getDataStore(dsConf);
    dsConf.put("isProducer", "false");
    DataStore consumerDS = DataStoreFinder.getDataStore(dsConf);

    // verify that we got back our KafkaDataStore objects properly
    if (producerDS == null) {
        throw new Exception("Null producer KafkaDataStore");
    }//from ww w.  ja  v a2  s  . c  o m
    if (consumerDS == null) {
        throw new Exception("Null consumer KafkaDataStore");
    }

    // create the schema which creates a topic in Kafka
    // (only needs to be done once)
    final String sftName = "KafkaQuickStart10";
    final String sftSchema = "name:String,age:Int,dtg:Date,*geom:Point:srid=4326";
    SimpleFeatureType sft = SimpleFeatureTypes.createType(sftName, sftSchema);
    // set zkPath to default if not specified
    String zkPath = (dsConf.get(ZK_PATH) == null) ? "/geomesa/ds/kafka" : dsConf.get(ZK_PATH);
    SimpleFeatureType preppedOutputSft = KafkaDataStoreHelper.createStreamingSFT(sft, zkPath);
    // only create the schema if it hasn't been created already
    if (!Arrays.asList(producerDS.getTypeNames()).contains(sftName))
        producerDS.createSchema(preppedOutputSft);
    if (!cmd.hasOption("automated")) {
        System.out.println("Register KafkaDataStore in GeoServer (Press enter to continue)");
        System.in.read();
    }

    // the live consumer must be created before the producer writes features
    // in order to read streaming data.
    // i.e. the live consumer will only read data written after its instantiation
    SimpleFeatureSource consumerFS = consumerDS.getFeatureSource(sftName);
    SimpleFeatureStore producerFS = (SimpleFeatureStore) producerDS.getFeatureSource(sftName);

    // creates and adds SimpleFeatures to the producer every 1/5th of a second
    System.out.println("Writing features to Kafka... refresh GeoServer layer preview to see changes");
    Instant replayStart = new Instant();

    String vis = cmd.getOptionValue(VISIBILITY);
    if (vis != null)
        System.out.println("Writing features with " + vis);
    addSimpleFeatures(sft, producerFS, vis);
    Instant replayEnd = new Instant();

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    SimpleFeatureCollection featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    addDeleteNewFeature(sft, producerFS);

    // read from Kafka after writing all the features.
    // LIVE CONSUMER - will obtain the current state of SimpleFeatures
    System.out.println("\nConsuming with the live consumer...");
    featureCollection = consumerFS.getFeatures();
    System.out.println(featureCollection.size() + " features were written to Kafka");

    // the state of the two SimpleFeatures is real time here
    System.out.println("Here are the two SimpleFeatures that were obtained with the live consumer:");
    SimpleFeatureIterator featureIterator = featureCollection.features();
    SimpleFeature feature1 = featureIterator.next();
    SimpleFeature feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    // REPLAY CONSUMER - will obtain the state of SimpleFeatures at any specified time
    // Replay consumer requires a ReplayConfig which takes a time range and a
    // duration of time to process
    System.out.println("\nConsuming with the replay consumer...");
    Duration readBehind = new Duration(1000); // 1 second readBehind
    ReplayConfig rc = new ReplayConfig(replayStart, replayEnd, readBehind);
    SimpleFeatureType replaySFT = KafkaDataStoreHelper.createReplaySFT(preppedOutputSft, rc);
    producerDS.createSchema(replaySFT);
    SimpleFeatureSource replayConsumerFS = consumerDS.getFeatureSource(replaySFT.getName());

    // querying for the state of SimpleFeatures approximately 5 seconds before the replayEnd.
    // the ReplayKafkaConsumerFeatureSource will build the state of SimpleFeatures
    // by processing all of the messages that were sent in between queryTime-readBehind and queryTime.
    // only the messages in between replayStart and replayEnd are cached.
    Instant queryTime = replayEnd.minus(5000);
    featureCollection = replayConsumerFS.getFeatures(ReplayTimeHelper.toFilter(queryTime));
    System.out.println(featureCollection.size() + " features were written to Kafka");

    System.out.println("Here are the two SimpleFeatures that were obtained with the replay consumer:");
    featureIterator = featureCollection.features();
    feature1 = featureIterator.next();
    feature2 = featureIterator.next();
    featureIterator.close();
    printFeature(feature1);
    printFeature(feature2);

    if (System.getProperty("clear") != null) {
        // Run Java command with -Dclear=true
        // This will cause a 'clear'
        producerFS.removeFeatures(Filter.INCLUDE);
    }

    System.exit(0);
}

---

From source file:com.google.cloud.dataflow.examples.opinionanalysis.IndexerPipelineUtils.java

License:Apache License

public static String buildBigQueryProcessedUrlsQuery(IndexerPipelineOptions options) {
    String timeWindow = null;//from   w  w w  .j a v a 2 s . com

    if (options.getProcessedUrlHistorySec() != null) {
        if (options.getProcessedUrlHistorySec() != Integer.MAX_VALUE) {
            Instant fromTime = Instant.now();
            fromTime = fromTime.minus(options.getProcessedUrlHistorySec() * 1000L);
            Integer fromDateId = IdConverterUtils.getDateIdFromTimestamp(fromTime.getMillis());
            timeWindow = "PublicationDateId >= " + fromDateId;
        }
    }

    if (timeWindow != null)
        timeWindow = "WHERE " + timeWindow;

    String result = "SELECT Url, MAX(ProcessingTime) AS ProcessingTime\n" + "FROM "
            + options.getBigQueryDataset() + "." + WEBRESOURCE_TABLE + "\n" + timeWindow + "\n"
            + "GROUP BY Url";

    return result;
}

---

From source file:com.google.cloud.dataflow.examples.opinionanalysis.IndexerPipelineUtils.java

License:Apache License

public static String buildBigQueryProcessedDocsQuery(IndexerPipelineOptions options) {
    String timeWindow = null;//  ww  w  .j ava  2 s.  c  o  m

    if (options.getProcessedUrlHistorySec() != null) {
        if (options.getProcessedUrlHistorySec() != Integer.MAX_VALUE) {
            Instant fromTime = Instant.now();
            fromTime = fromTime.minus(options.getProcessedUrlHistorySec() * 1000L);
            Integer fromDateId = IdConverterUtils.getDateIdFromTimestamp(fromTime.getMillis());
            timeWindow = "PublicationDateId >= " + fromDateId;
        }
    }

    if (timeWindow != null)
        timeWindow = "WHERE " + timeWindow;

    String result = "SELECT DocumentHash, MAX(ProcessingTime) AS ProcessingTime\n" + "FROM "
            + options.getBigQueryDataset() + "." + DOCUMENT_TABLE + "\n" + timeWindow + "\n"
            + "GROUP BY DocumentHash";

    return result;
}

---

From source file:com.google.cloud.dataflow.examples.opinionanalysis.IndexerPipelineUtils.java

License:Apache License

public static String buildBigQueryProcessedSocialCountsQuery(IndexerPipelineOptions options) {
    String timeWindow = null;/*w w  w  .  j  a v  a 2  s .  co  m*/

    if (options.getWrSocialCountHistoryWindowSec() != null) {
        if (options.getWrSocialCountHistoryWindowSec() != Integer.MAX_VALUE) {
            Instant fromTime = Instant.now();
            fromTime = fromTime.minus(options.getWrSocialCountHistoryWindowSec() * 1000L);
            Integer fromDateId = IdConverterUtils.getDateIdFromTimestamp(fromTime.getMillis());
            timeWindow = "WrPublicationDateId >= " + fromDateId;
        }
    }

    if (timeWindow != null)
        timeWindow = "WHERE " + timeWindow;

    String result = "SELECT WebResourceHash, MAX(CountTime) AS LastCountTime\n" + "FROM "
            + options.getBigQueryDataset() + "." + WRSOCIALCOUNT_TABLE + "\n" + timeWindow + "\n"
            + "GROUP BY WebResourceHash";

    return result;

}

---

From source file:com.google.cloud.dataflow.sdk.transforms.windowing.SlidingWindows.java

License:Apache License

@Override
public Collection<IntervalWindow> assignWindows(AssignContext c) {
    List<IntervalWindow> windows = new ArrayList<>((int) (size.getMillis() / period.getMillis()));
    Instant timestamp = c.timestamp();
    long lastStart = lastStartFor(timestamp);
    for (long start = lastStart; start > timestamp.minus(size).getMillis(); start -= period.getMillis()) {
        windows.add(new IntervalWindow(new Instant(start), size));
    }/*from   w w w  .  j  a  v a  2 s . c o m*/
    return windows;
}

---

From source file:com.google.cloud.pubsub.spi.v1.MessageDispatcher.java

License:Open Source License

private void setupNextAckDeadlineExtensionAlarm(Instant expiration) {
    Instant possibleNextAlarmTime = expiration.minus(ackExpirationPadding);
    alarmsLock.lock();//from   ww w  .  j a v  a 2  s .  com
    try {
        if (nextAckDeadlineExtensionAlarmTime.isAfter(possibleNextAlarmTime)) {
            logger.log(Level.INFO, "Scheduling next alarm time: " + possibleNextAlarmTime
                    + ", last alarm set to time: " + nextAckDeadlineExtensionAlarmTime);
            if (ackDeadlineExtensionAlarm != null) {
                logger.log(Level.INFO, "Canceling previous alarm");
                ackDeadlineExtensionAlarm.cancel(false);
            }

            nextAckDeadlineExtensionAlarmTime = possibleNextAlarmTime;

            ackDeadlineExtensionAlarm = executor.schedule(new AckDeadlineAlarm(),
                    nextAckDeadlineExtensionAlarmTime.getMillis() - clock.millis(), TimeUnit.MILLISECONDS);
        }

    } finally {
        alarmsLock.unlock();
    }
}

---

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