org.apache.beam.sdk.metrics.Counter Java Examples

private PTransform<? super PCollection<Row>, PCollection<Row>> logBytesMetric(
    final Coder<Row> coder) {

  return ParDo.of(
      new DoFn<Row, Row>() {
        private final Counter bytesMetric = Metrics.counter(name, "bytes");

        @ProcessElement
        public void processElement(@Element Row element, OutputReceiver<Row> o)
            throws IOException {
          ByteArrayOutputStream outStream = new ByteArrayOutputStream();
          coder.encode(element, outStream, Coder.Context.OUTER);
          byte[] byteArray = outStream.toByteArray();
          bytesMetric.inc((long) byteArray.length);
          ByteArrayInputStream inStream = new ByteArrayInputStream(byteArray);
          Row row = coder.decode(inStream, Coder.Context.OUTER);
          o.output(row);
        }
      });
}
 

@Test
public void extractThrottleTimeCounters() {
  BatchModeExecutionContext executionContext =
      BatchModeExecutionContext.forTesting(PipelineOptionsFactory.create(), "testStage");
  DataflowOperationContext operationContext =
      executionContext.createOperationContext(NameContextsForTests.nameContextForTest());

  Counter counter =
      operationContext
          .metricsContainer()
          .getCounter(
              MetricName.named(
                  BatchModeExecutionContext.DATASTORE_THROTTLE_TIME_NAMESPACE,
                  "cumulativeThrottlingSeconds"));
  counter.inc(12);
  counter.inc(17);
  counter.inc(1);

  assertEquals(30L, (long) executionContext.extractThrottleTime());
}
 

@Test
public void testOperationsUpdateCounterFromContainerWhenContainerIsPresent() {
  HashMap<String, String> labels = new HashMap<String, String>();
  String urn = MonitoringInfoConstants.Urns.ELEMENT_COUNT;
  MonitoringInfoMetricName name = MonitoringInfoMetricName.named(urn, labels);

  MetricsContainer mockContainer = Mockito.mock(MetricsContainer.class);
  Counter mockCounter = Mockito.mock(Counter.class);
  when(mockContainer.getCounter(name)).thenReturn(mockCounter);

  Counter counter = LabeledMetrics.counter(name);

  MetricsEnvironment.setCurrentContainer(mockContainer);
  counter.inc();
  verify(mockCounter).inc(1);

  counter.inc(47L);
  verify(mockCounter).inc(47);

  counter.dec(5L);
  verify(mockCounter).inc(-5);
}
 

void commitTxn(long lastRecordId, Counter numTransactions) throws IOException {
  try {
    // Store id in consumer group metadata for the partition.
    // NOTE: Kafka keeps this metadata for 24 hours since the last update. This limits
    // how long the pipeline could be down before resuming it. It does not look like
    // this TTL can be adjusted (asked about it on Kafka users list).
    ProducerSpEL.sendOffsetsToTransaction(
        producer,
        ImmutableMap.of(
            new TopicPartition(spec.getTopic(), shard),
            new OffsetAndMetadata(
                0L,
                JSON_MAPPER.writeValueAsString(new ShardMetadata(lastRecordId, writerId)))),
        spec.getSinkGroupId());
    ProducerSpEL.commitTransaction(producer);

    numTransactions.inc();
    LOG.debug("{} : committed {} records", shard, lastRecordId - committedId);

    committedId = lastRecordId;
  } catch (KafkaException e) {
    ProducerSpEL.abortTransaction(producer);
    throw e;
  }
}
 

Future<RecordMetadata> sendRecord(
    TimestampedValue<ProducerRecord<K, V>> record, Counter sendCounter) {
  try {
    Long timestampMillis =
        spec.getPublishTimestampFunction() != null
            ? spec.getPublishTimestampFunction()
                .getTimestamp(record.getValue(), record.getTimestamp())
                .getMillis()
            : null;

    Future<RecordMetadata> result =
        producer.send(
            new ProducerRecord<>(
                spec.getTopic(),
                null,
                timestampMillis,
                record.getValue().key(),
                record.getValue().value()));
    sendCounter.inc();
    return result;
  } catch (KafkaException e) {
    ProducerSpEL.abortTransaction(producer);
    throw e;
  }
}
 

/** Factory method to create mapper instance. */
public static MapWithFailures<PubsubMessage, PubsubMessage, PubsubMessage> of(int maxBytes) {
  final Counter countPayloadTooLarge = Metrics.counter(LimitPayloadSize.class,
      "payload_too_large");
  return MapElements.into(TypeDescriptor.of(PubsubMessage.class)).via((PubsubMessage msg) -> {
    msg = PubsubConstraints.ensureNonNull(msg);
    int numBytes = msg.getPayload().length;
    if (numBytes > maxBytes) {
      countPayloadTooLarge.inc();
      throw new PayloadTooLargeException("Message payload is " + numBytes
          + "bytes, larger than the" + " configured limit of " + maxBytes);
    }
    return msg;
  }).exceptionsInto(TypeDescriptor.of(PubsubMessage.class))
      .exceptionsVia((ExceptionElement<PubsubMessage> ee) -> {
        try {
          throw ee.exception();
        } catch (PayloadTooLargeException e) {
          return FailureMessage.of(LimitPayloadSize.class.getSimpleName(), ee.element(),
              ee.exception());
        }
      });
}
 

@Override
public PCollection<Event> expand(PCollection<Event> events) {
  final Coder<Event> coder = events.getCoder();
  return events
      // Force round trip through coder.
      .apply(
      name + ".Serialize",
      ParDo.of(
          new DoFn<Event, Event>() {
            private final Counter bytesMetric = Metrics.counter(name, "bytes");

            @ProcessElement
            public void processElement(ProcessContext c) throws CoderException, IOException {
              ByteArrayOutputStream outStream = new ByteArrayOutputStream();
              coder.encode(c.element(), outStream, Coder.Context.OUTER);
              byte[] byteArray = outStream.toByteArray();
              bytesMetric.inc((long) byteArray.length);
              ByteArrayInputStream inStream = new ByteArrayInputStream(byteArray);
              Event event = coder.decode(inStream, Coder.Context.OUTER);
              c.output(event);
            }
          }));
}
 

/** Generate Avro schema by reading one row. Expose Beam metrics via a Beam PTransform. */
public static Schema createSchema(
    final Pipeline pipeline, final JdbcExportArgs args, final Connection connection)
    throws Exception {
  final long startTime = System.nanoTime();
  final Schema generatedSchema = generateAvroSchema(args, connection);
  final long elapsedTimeSchema = (System.nanoTime() - startTime) / 1000000;
  LOGGER.info("Elapsed time to schema {} seconds", elapsedTimeSchema / 1000.0);

  final Counter cnt =
      Metrics.counter(BeamJdbcAvroSchema.class.getCanonicalName(), "schemaElapsedTimeMs");
  pipeline
      .apply(
          "ExposeSchemaCountersSeed",
          Create.of(Collections.singletonList(0)).withType(TypeDescriptors.integers()))
      .apply(
          "ExposeSchemaCounters",
          MapElements.into(TypeDescriptors.integers())
              .via(
                  v -> {
                    cnt.inc(elapsedTimeSchema);
                    return v;
                  }));
  return generatedSchema;
}
 

@VisibleForTesting
static Counter getOrCreateCounter(@Nullable Map<String, String> attributes, String name) {
  if (attributes == null) {
    attributes = EMPTY_ATTRIBUTES;
  }
  String namespace = attributes.getOrDefault("document_namespace", "unknown_namespace");
  // Dataflow's UI collapses the metric name, but always shows the penultimate path component
  // as part of "Step", so we're a bit more verbose with the default doctype value.
  String docType = attributes.getOrDefault("document_type", "unknown_doctype");
  String version = attributes.get("document_version");
  if (version != null) {
    docType = docType + "_v" + version;
  }
  String key = String.format("%s/%s/%s", namespace, docType, name)
      // We change dashes to underscores to make sure we're following Stackdriver's naming scheme:
      // https://cloud.google.com/monitoring/api/v3/metrics-details#label_names
      .replace("-", "_");
  return counters.computeIfAbsent(key, k -> Metrics.counter(PerDocTypeCounter.class, k));
}
 

Future<RecordMetadata> sendRecord(TimestampedValue<KV<K, V>> record, Counter sendCounter) {
  try {
    Long timestampMillis =
        spec.getPublishTimestampFunction() != null
            ? spec.getPublishTimestampFunction()
                .getTimestamp(record.getValue(), record.getTimestamp())
                .getMillis()
            : null;

    Future<RecordMetadata> result =
        producer.send(
            new ProducerRecord<>(
                spec.getTopic(),
                null,
                timestampMillis,
                record.getValue().getKey(),
                record.getValue().getValue()));
    sendCounter.inc();
    return result;
  } catch (KafkaException e) {
    ProducerSpEL.abortTransaction(producer);
    throw e;
  }
}
 

void commitTxn(long lastRecordId, Counter numTransactions) throws IOException {
  try {
    // Store id in consumer group metadata for the partition.
    // NOTE: Kafka keeps this metadata for 24 hours since the last update. This limits
    // how long the pipeline could be down before resuming it. It does not look like
    // this TTL can be adjusted (asked about it on Kafka users list).
    ProducerSpEL.sendOffsetsToTransaction(
        producer,
        ImmutableMap.of(
            new TopicPartition(spec.getTopic(), shard),
            new OffsetAndMetadata(
                0L,
                JSON_MAPPER.writeValueAsString(new ShardMetadata(lastRecordId, writerId)))),
        spec.getSinkGroupId());
    ProducerSpEL.commitTransaction(producer);

    numTransactions.inc();
    LOG.debug("{} : committed {} records", shard, lastRecordId - committedId);

    committedId = lastRecordId;
  } catch (KafkaException e) {
    ProducerSpEL.abortTransaction(producer);
    throw e;
  }
}
 

@Test
@Category({NeedsRunner.class, UsesCommittedMetrics.class, UsesCounterMetrics.class})
public void testRunPTransform() {
  final String namespace = PipelineRunnerTest.class.getName();
  final Counter counter = Metrics.counter(namespace, "count");
  final PipelineResult result =
      PipelineRunner.fromOptions(p.getOptions())
          .run(
              new PTransform<PBegin, POutput>() {
                @Override
                public POutput expand(PBegin input) {
                  PCollection<Double> output =
                      input
                          .apply(Create.of(1, 2, 3, 4))
                          .apply("ScaleByTwo", MapElements.via(new ScaleFn<>(2.0, counter)));
                  PAssert.that(output).containsInAnyOrder(2.0, 4.0, 6.0, 8.0);
                  return output;
                }
              });

  // Checking counters to verify the pipeline actually ran.
  assertThat(
      result
          .metrics()
          .queryMetrics(
              MetricsFilter.builder()
                  .addNameFilter(MetricNameFilter.inNamespace(namespace))
                  .build())
          .getCounters(),
      hasItem(metricsResult(namespace, "count", "ScaleByTwo", 4L, true)));
}
 

@Test
public void getCounterTest() {
  Map<String, String> attributes = ImmutableMap //
      .of("document_namespace", "telemetry", //
          "document_type", "core", //
          "document_version", "10");
  Counter counter = PerDocTypeCounter.getOrCreateCounter(attributes, "my-name");
  assertEquals("telemetry/core_v10/my_name", counter.getName().getName());
}
 

@Test
public void testCounterDoesNotFailOperationsWhenNoMetricsContainerPresent() {
  MetricsEnvironment.setCurrentContainer(null);
  assertNull(MetricsEnvironment.getCurrentContainer());
  HashMap<String, String> labels = new HashMap<String, String>();
  String urn = MonitoringInfoConstants.Urns.ELEMENT_COUNT;
  MonitoringInfoMetricName name = MonitoringInfoMetricName.named(urn, labels);

  Counter counter = LabeledMetrics.counter(name);
  counter.inc();
  counter.inc(5L);
  counter.dec();
  counter.dec(5L);
}
 

@Test
public void getCounterVersionlessTest() {
  Map<String, String> attributes = ImmutableMap //
      .of("document_namespace", "telemetry", //
          "document_type", "core");
  Counter counter = PerDocTypeCounter.getOrCreateCounter(attributes, "my-name");
  assertEquals("telemetry/core/my_name", counter.getName().getName());
}
 

@ProcessElement
public void processElement(ProcessContext processContext) {
  for (int i = 0; i < numberOfOperations; i++) {
    for (Counter counter : counters) {
      counter.inc();
    }
  }
  processContext.output(processContext.element());
}
 

/** Return a transform to format each element as a string. */
public static <T> ParDo.SingleOutput<T, String> format(final String name) {
  return ParDo.of(
      new DoFn<T, String>() {
        final Counter recordCounterMetric = Metrics.counter(name, "records");

        @ProcessElement
        public void processElement(ProcessContext c) {
          recordCounterMetric.inc();
          c.output(c.element().toString());
        }
      });
}
 

/** Return a transform to count and discard each element. */
public static <T> ParDo.SingleOutput<T, Void> devNull(final String name) {
  return ParDo.of(
      new DoFn<T, Void>() {
        final Counter discardedCounterMetric = Metrics.counter(name, "discarded");

        @ProcessElement
        public void processElement(ProcessContext c) {
          discardedCounterMetric.inc();
        }
      });
}
 

/** Return a transform to pass-through events, but count them as they go by. */
public static ParDo.SingleOutput<Event, Event> snoop(final String name) {
  return ParDo.of(
      new DoFn<Event, Event>() {
        final Counter eventCounter = Metrics.counter(name, "events");
        final Counter newPersonCounter = Metrics.counter(name, "newPersons");
        final Counter newAuctionCounter = Metrics.counter(name, "newAuctions");
        final Counter bidCounter = Metrics.counter(name, "bids");
        final Counter endOfStreamCounter = Metrics.counter(name, "endOfStream");

        @ProcessElement
        public void processElement(ProcessContext c) {
          eventCounter.inc();
          if (c.element().newPerson != null) {
            newPersonCounter.inc();
          } else if (c.element().newAuction != null) {
            newAuctionCounter.inc();
          } else if (c.element().bid != null) {
            bidCounter.inc();
          } else {
            endOfStreamCounter.inc();
          }
          info("%s snooping element %s", name, c.element());
          c.output(c.element());
        }
      });
}
 

@Override
public PCollection<AuctionBid> expand(PCollection<Event> events) {
  // Window auctions and bids into custom auction windows. New people events will be discarded.
  // This will allow us to bring bids and auctions together irrespective of how long
  // each auction is open for.
  events = events.apply("Window", Window.into(auctionOrBidWindowFn));

  // Key auctions by their id.
  PCollection<KV<Long, Auction>> auctionsById =
      events
          .apply(NexmarkQueryUtil.JUST_NEW_AUCTIONS)
          .apply("AuctionById:", NexmarkQueryUtil.AUCTION_BY_ID);

  // Key bids by their auction id.
  PCollection<KV<Long, Bid>> bidsByAuctionId =
      events
          .apply(NexmarkQueryUtil.JUST_BIDS)
          .apply("BidByAuction", NexmarkQueryUtil.BID_BY_AUCTION);

  // Find the highest price valid bid for each closed auction.
  return
  // Join auctions and bids.
  KeyedPCollectionTuple.of(NexmarkQueryUtil.AUCTION_TAG, auctionsById)
      .and(NexmarkQueryUtil.BID_TAG, bidsByAuctionId)
      .apply(CoGroupByKey.create())
      // Filter and select.
      .apply(
          name + ".Join",
          ParDo.of(
              new DoFn<KV<Long, CoGbkResult>, AuctionBid>() {
                private final Counter noAuctionCounter = Metrics.counter(name, "noAuction");
                private final Counter underReserveCounter = Metrics.counter(name, "underReserve");
                private final Counter noValidBidsCounter = Metrics.counter(name, "noValidBids");

                @ProcessElement
                public void processElement(ProcessContext c) {
                  @Nullable
                  Auction auction =
                      c.element().getValue().getOnly(NexmarkQueryUtil.AUCTION_TAG, null);
                  if (auction == null) {
                    // We have bids without a matching auction. Give up.
                    noAuctionCounter.inc();
                    return;
                  }
                  // Find the current winning bid for auction.
                  // The earliest bid with the maximum price above the reserve wins.
                  Bid bestBid = null;
                  for (Bid bid : c.element().getValue().getAll(NexmarkQueryUtil.BID_TAG)) {
                    // Bids too late for their auction will have been
                    // filtered out by the window merge function.
                    checkState(bid.dateTime.compareTo(auction.expires) < 0);
                    if (bid.price < auction.reserve) {
                      // Bid price is below auction reserve.
                      underReserveCounter.inc();
                      continue;
                    }

                    if (bestBid == null
                        || Bid.PRICE_THEN_DESCENDING_TIME.compare(bid, bestBid) > 0) {
                      bestBid = bid;
                    }
                  }
                  if (bestBid == null) {
                    // We don't have any valid bids for auction.
                    noValidBidsCounter.inc();
                    return;
                  }
                  c.output(new AuctionBid(auction, bestBid));
                }
              }));
}
 

public ScaleFn(double scalar, Counter counter) {
  this.scalar = scalar;
  this.counter = counter;
}
 

@Override
public PCollection<KV<String, Integer>> expand(PCollection<KV<String, Integer>> userScores) {

  // Get the sum of scores for each user.
  PCollection<KV<String, Integer>> sumScores =
      userScores.apply("UserSum", Sum.integersPerKey());

  // Extract the score from each element, and use it to find the global mean.
  final PCollectionView<Double> globalMeanScore =
      sumScores.apply(Values.create()).apply(Mean.<Integer>globally().asSingletonView());

  // Filter the user sums using the global mean.
  PCollection<KV<String, Integer>> filtered =
      sumScores.apply(
          "ProcessAndFilter",
          ParDo
              // use the derived mean total score as a side input
              .of(
                  new DoFn<KV<String, Integer>, KV<String, Integer>>() {
                    private final Counter numSpammerUsers =
                        Metrics.counter("main", "SpammerUsers");

                    @ProcessElement
                    public void processElement(ProcessContext c) {
                      Integer score = c.element().getValue();
                      Double gmc = c.sideInput(globalMeanScore);
                      if (score > (gmc * SCORE_WEIGHT)) {
                        LOG.info(
                            "user "
                                + c.element().getKey()
                                + " spammer score "
                                + score
                                + " with mean "
                                + gmc);
                        numSpammerUsers.inc();
                        c.output(c.element());
                      }
                    }
                  })
              .withSideInputs(globalMeanScore));
  return filtered;
}
 

@Test
public void getCounterNullTest() {
  Counter counter = PerDocTypeCounter.getOrCreateCounter(null, "my-name");
  assertEquals("unknown_namespace/unknown_doctype/my_name", counter.getName().getName());
}
 

/**
 * Create a metric that can be incremented and decremented, and is aggregated by taking the sum.
 */
public static Counter counter(MonitoringInfoMetricName metricName) {
  return new DelegatingCounter(metricName);
}
 

@Override
public Counter getCounter(MetricName metricName) {
  return counters.computeIfAbsent(metricName, CounterImpl::new);
}
 

@Override
public Counter getCounter(MetricName metricName) {
  return counters.get(metricName);
}
 

@Override
public Counter getCounter(MetricName metricName) {
  return getCurrentContainer().getCounter(metricName);
}
 

@Test
public void extractMetricUpdatesCounter() {
  BatchModeExecutionContext executionContext =
      BatchModeExecutionContext.forTesting(PipelineOptionsFactory.create(), "testStage");
  DataflowOperationContext operationContext =
      executionContext.createOperationContext(NameContextsForTests.nameContextForTest());

  Counter counter =
      operationContext
          .metricsContainer()
          .getCounter(MetricName.named("namespace", "some-counter"));
  counter.inc(1);
  counter.inc(41);
  counter.inc(1);
  counter.inc(-1);

  final CounterUpdate expected =
      new CounterUpdate()
          .setStructuredNameAndMetadata(
              new CounterStructuredNameAndMetadata()
                  .setName(
                      new CounterStructuredName()
                          .setOrigin("USER")
                          .setOriginNamespace("namespace")
                          .setName("some-counter")
                          .setOriginalStepName("originalName"))
                  .setMetadata(new CounterMetadata().setKind(Kind.SUM.toString())))
          .setCumulative(true)
          .setInteger(longToSplitInt(42));

  assertThat(executionContext.extractMetricUpdates(false), containsInAnyOrder(expected));

  executionContext.commitMetricUpdates();

  Counter counterUncommitted =
      operationContext
          .metricsContainer()
          .getCounter(MetricName.named("namespace", "uncommitted-counter"));
  counterUncommitted.inc(64);

  final CounterUpdate expectedUncommitted =
      new CounterUpdate()
          .setStructuredNameAndMetadata(
              new CounterStructuredNameAndMetadata()
                  .setName(
                      new CounterStructuredName()
                          .setOrigin("USER")
                          .setOriginNamespace("namespace")
                          .setName("uncommitted-counter")
                          .setOriginalStepName("originalName"))
                  .setMetadata(new CounterMetadata().setKind(Kind.SUM.toString())))
          .setCumulative(true)
          .setInteger(longToSplitInt(64));

  // Expect to get only the uncommitted metric, unless final update.
  assertThat(
      executionContext.extractMetricUpdates(false), containsInAnyOrder(expectedUncommitted));
  assertThat(
      executionContext.extractMetricUpdates(true),
      containsInAnyOrder(expected, expectedUncommitted));

  executionContext.commitMetricUpdates();
  // All Metrics are committed, expect none unless final update.
  assertThat(executionContext.extractMetricUpdates(false), emptyIterable());
  assertThat(
      executionContext.extractMetricUpdates(true),
      containsInAnyOrder(expected, expectedUncommitted));
}
 

@Override
public PCollection<KV<String, Integer>> expand(PCollection<KV<String, Integer>> userScores) {

  // Get the sum of scores for each user.
  PCollection<KV<String, Integer>> sumScores =
      userScores.apply("UserSum", Sum.integersPerKey());

  // Extract the score from each element, and use it to find the global mean.
  final PCollectionView<Double> globalMeanScore =
      sumScores.apply(Values.create()).apply(Mean.<Integer>globally().asSingletonView());

  // Filter the user sums using the global mean.
  PCollection<KV<String, Integer>> filtered =
      sumScores.apply(
          "ProcessAndFilter",
          ParDo
              // use the derived mean total score as a side input
              .of(
                  new DoFn<KV<String, Integer>, KV<String, Integer>>() {
                    private final Counter numSpammerUsers =
                        Metrics.counter("main", "SpammerUsers");

                    @ProcessElement
                    public void processElement(ProcessContext c) {
                      Integer score = c.element().getValue();
                      Double gmc = c.sideInput(globalMeanScore);
                      if (score > (gmc * SCORE_WEIGHT)) {
                        LOG.info(
                            "user "
                                + c.element().getKey()
                                + " spammer score "
                                + score
                                + " with mean "
                                + gmc);
                        numSpammerUsers.inc();
                        c.output(c.element());
                      }
                    }
                  })
              .withSideInputs(globalMeanScore));
  return filtered;
}