Merge pull request #37769: [ErrorProne] Enable LongDoubleConversion check

Author: kennknowles

buildSrc/src/main/groovy/org/apache/beam/gradle/BeamModulePlugin.groovy

@@ -1572,7 +1572,6 @@ class BeamModulePlugin implements Plugin<Project> {
             "DirectInvocationOnMock",
             "Finalize",
             "JUnitIncompatibleType",
-            "LongDoubleConversion",
             "MockNotUsedInProduction",
             "NarrowCalculation",
             "NullableTypeParameter",

it/google-cloud-platform/src/test/java/org/apache/beam/it/gcp/bigquery/BigQueryIOLT.java

@@ -341,7 +341,7 @@ private void testRead() throws IOException {
             region,
             launchInfo.jobId(),
             getBeamMetricsName(PipelineMetricsType.COUNTER, READ_ELEMENT_METRIC_NAME));
-    assertEquals(configuration.numRecords, numRecords, 0.5);
+    assertEquals((double) configuration.numRecords, numRecords, 0.5);
 
     // export metrics
     MetricsConfiguration metricsConfig =

it/google-cloud-platform/src/test/java/org/apache/beam/it/gcp/spanner/SpannerIOLT.java

@@ -156,7 +156,7 @@ public void testSpannerWriteAndRead() throws IOException {
             region,
             readInfo.jobId(),
             getBeamMetricsName(PipelineMetricsType.COUNTER, READ_ELEMENT_METRIC_NAME));
-    assertEquals(configuration.numRecords, numRecords, 0.5);
+    assertEquals((double) configuration.numRecords, numRecords, 0.5);
 
     // export metrics
     MetricsConfiguration metricsConfig =

it/google-cloud-platform/src/test/java/org/apache/beam/it/gcp/storage/FileBasedIOLT.java

@@ -221,7 +221,7 @@ public void testTextIOWriteThenRead() throws IOException {
             readInfo.jobId(),
             getBeamMetricsName(PipelineMetricsType.COUNTER, READ_ELEMENT_METRIC_NAME));
 
-    assertEquals(configuration.numRecords, numRecords, 0.5);
+    assertEquals((double) configuration.numRecords, numRecords, 0.5);
 
     // export metrics
     MetricsConfiguration metricsConfig =

runners/direct-java/src/main/java/org/apache/beam/runners/direct/WriteWithShardingFactory.java

@@ -138,7 +138,7 @@ private int calculateShards(long totalRecords) {
         return (int) totalRecords;
       }
       // 100mil records before >7 output files
-      int floorLogRecs = (int) Math.log10(totalRecords);
+      int floorLogRecs = (int) Math.log10((double) totalRecords);
       return Math.max(floorLogRecs, MIN_SHARDS_FOR_LOG) + extraShards;
     }
   }

runners/google-cloud-dataflow-java/worker/src/main/java/org/apache/beam/runners/dataflow/worker/WorkerCustomSources.java

@@ -661,7 +661,7 @@ public void close() throws IOException {
     @VisibleForTesting
     static @Nullable ReportedParallelism longToParallelism(long value) {
       if (value >= 0) {
-        return new ReportedParallelism().setValue(Double.valueOf(value));
+        return new ReportedParallelism().setValue(Double.valueOf((double) value));
       } else {
         return null;
       }

runners/google-cloud-dataflow-java/worker/src/main/java/org/apache/beam/runners/dataflow/worker/counters/CounterFactory.java

@@ -226,7 +226,7 @@ public final CounterDistribution addValue(long value) {
       long count = this.getCount() + 1;
       long sum = this.getSum() + value;
       // TODO: Replace sum-of-squares with statistics for a better stddev algorithm.
-      double sumOfSquares = this.getSumOfSquares() + Math.pow(value, 2);
+      double sumOfSquares = this.getSumOfSquares() + Math.pow((double) value, 2);
 
       int bucketIndex = calculateBucket(value);
       List<Long> buckets = incrementBucket(bucketIndex);

sdks/java/core/src/main/java/org/apache/beam/sdk/io/Read.java

@@ -298,7 +298,7 @@ public void splitRestriction(
         desiredChunkSize = 64 << 20; // 64mb
       } else {
         // 1mb --> 1 shard; 1gb --> 32 shards; 1tb --> 1000 shards, 1pb --> 32k shards
-        desiredChunkSize = Math.max(1 << 20, (long) (1000 * Math.sqrt(estimatedSize)));
+        desiredChunkSize = Math.max(1 << 20, (long) (1000 * Math.sqrt((double) estimatedSize)));
       }
       List<BoundedSourceT> splits =
           (List<BoundedSourceT>) restriction.split(desiredChunkSize, pipelineOptions);
@@ -1079,7 +1079,7 @@ private Progress tryGetProgressOrThrow() throws IOException {
           if (size != UnboundedReader.BACKLOG_UNKNOWN) {
             // The UnboundedSource/UnboundedReader API has no way of reporting how much work
             // has been completed so runners can only see the work remaining changing.
-            return Progress.from(0, size);
+            return Progress.from(0, (double) size);
           }
 
           // TODO: Support "global" backlog reporting

sdks/java/core/src/main/java/org/apache/beam/sdk/transforms/ApproximateQuantiles.java

@@ -277,7 +277,7 @@ public ApproximateQuantilesCombineFn<T, ComparatorT> withEpsilon(double epsilon)
      * of {@code maxNumElements}.
      */
     public ApproximateQuantilesCombineFn<T, ComparatorT> withMaxInputSize(long maxNumElements) {
-      return create(numQuantiles, compareFn, maxNumElements, maxNumElements);
+      return create(numQuantiles, compareFn, maxNumElements, (double) maxNumElements);
     }
 
     /**
@@ -484,7 +484,8 @@ private QuantileBuffer<T> collapse(Iterable<QuantileBuffer<T>> buffers) {
         newLevel = Math.max(newLevel, buffer.level + 1);
         newWeight += buffer.weight;
       }
-      List<T> newElements = interpolate(buffers, bufferSize, newWeight, offset(newWeight));
+      List<T> newElements =
+          interpolate(buffers, bufferSize, (double) newWeight, (double) offset(newWeight));
       return new QuantileBuffer<>(newLevel, newWeight, newElements);
     }
 

sdks/java/core/src/main/java/org/apache/beam/sdk/util/FluentBackoff.java

@@ -234,7 +234,7 @@ public long nextBackOffMillis() {
           Math.min(
               backoffConfig.initialBackoff.getMillis()
                   * Math.pow(backoffConfig.exponent, currentRetry),
-              backoffConfig.maxBackoff.getMillis());
+              (double) backoffConfig.maxBackoff.getMillis());
       double randomOffset =
           (Math.random() * 2 - 1) * DEFAULT_RANDOMIZATION_FACTOR * currentIntervalMillis;
       long nextBackoffMillis = Math.round(currentIntervalMillis + randomOffset);