diff --git a/google-cloud-bigtable/clirr-ignored-differences.xml b/google-cloud-bigtable/clirr-ignored-differences.xml
index 9391d2ea8..ab921a973 100644
--- a/google-cloud-bigtable/clirr-ignored-differences.xml
+++ b/google-cloud-bigtable/clirr-ignored-differences.xml
@@ -23,10 +23,4 @@
8001com/google/cloud/bigtable/gaxx/tracing/WrappedTracerFactory*
-
-
- 7004
- com/google/cloud/bigtable/data/v2/stub/EnhancedBigtableStub
- *
-
-
+
\ No newline at end of file
diff --git a/google-cloud-bigtable/src/main/java/com/google/cloud/bigtable/data/v2/BigtableDataClient.java b/google-cloud-bigtable/src/main/java/com/google/cloud/bigtable/data/v2/BigtableDataClient.java
index ce9a57fa7..04e1b1598 100644
--- a/google-cloud-bigtable/src/main/java/com/google/cloud/bigtable/data/v2/BigtableDataClient.java
+++ b/google-cloud-bigtable/src/main/java/com/google/cloud/bigtable/data/v2/BigtableDataClient.java
@@ -23,7 +23,6 @@
import com.google.api.core.BetaApi;
import com.google.api.core.InternalApi;
import com.google.api.gax.batching.Batcher;
-import com.google.api.gax.grpc.GrpcCallContext;
import com.google.api.gax.rpc.ApiExceptions;
import com.google.api.gax.rpc.ResponseObserver;
import com.google.api.gax.rpc.ServerStream;
@@ -1074,40 +1073,7 @@ public void bulkMutateRows(BulkMutation mutation) {
*/
@BetaApi("This surface is likely to change as the batching surface evolves.")
public Batcher newBulkMutationBatcher(@Nonnull String tableId) {
- return newBulkMutationBatcher(tableId, null);
- }
-
- /**
- * Mutates multiple rows in a batch. Each individual row is mutated atomically as in MutateRow,
- * but the entire batch is not executed atomically. The returned Batcher instance is not
- * threadsafe, it can only be used from single thread. This method allows customization of the
- * underlying RPCs by passing in a {@link com.google.api.gax.grpc.GrpcCallContext}. The same
- * context will be reused for all batches. This can be used to customize things like per attempt
- * timeouts.
- *
- *
Sample Code:
- *
- *
{@code
- * try (BigtableDataClient bigtableDataClient = BigtableDataClient.create("[PROJECT]", "[INSTANCE]")) {
- * try (Batcher batcher = bigtableDataClient.newBulkMutationBatcher("[TABLE]", GrpcCallContext.createDefault().withTimeout(Duration.ofSeconds(10)))) {
- * for (String someValue : someCollection) {
- * ApiFuture entryFuture =
- * batcher.add(
- * RowMutationEntry.create("[ROW KEY]")
- * .setCell("[FAMILY NAME]", "[QUALIFIER]", "[VALUE]"));
- * }
- *
- * // Blocks until mutations are applied on all submitted row entries.
- * batcher.flush();
- * }
- * // Before `batcher` is closed, all remaining(If any) mutations are applied.
- * }
- * }
- */
- @BetaApi("This surface is likely to change as the batching surface evolves.")
- public Batcher newBulkMutationBatcher(
- @Nonnull String tableId, @Nullable GrpcCallContext ctx) {
- return stub.newMutateRowsBatcher(tableId, ctx);
+ return stub.newMutateRowsBatcher(tableId);
}
/**
@@ -1193,61 +1159,11 @@ public Batcher newBulkReadRowsBatcher(String tableId) {
*/
public Batcher newBulkReadRowsBatcher(
String tableId, @Nullable Filters.Filter filter) {
- return newBulkReadRowsBatcher(tableId, filter, null);
- }
-
- /**
- * Reads rows for given tableId and filter criteria in a batch. If the row does not exist, the
- * value will be null. The returned Batcher instance is not threadsafe, it can only be used from a
- * single thread. This method allows customization of the underlying RPCs by passing in a {@link
- * com.google.api.gax.grpc.GrpcCallContext}. The same context will be reused for all batches. This
- * can be used to customize things like per attempt timeouts.
- *
- *
Performance notice: The ReadRows protocol requires that rows are sent in ascending key
- * order, which means that the keys are processed sequentially on the server-side, so batching
- * allows improving throughput but not latency. Lower latencies can be achieved by sending smaller
- * requests concurrently.
- *
- *
Sample Code:
- *
- *
{@code
- * try (BigtableDataClient bigtableDataClient = BigtableDataClient.create("[PROJECT]", "[INSTANCE]")) {
- *
- * // Build the filter expression
- * Filter filter = FILTERS.chain()
- * .filter(FILTERS.key().regex("prefix.*"))
- * .filter(FILTERS.limit().cellsPerRow(10));
- *
- * List> rows = new ArrayList<>();
- *
- * try (Batcher batcher = bigtableDataClient.newBulkReadRowsBatcher(
- * "[TABLE]", filter, GrpcCallContext.createDefault().withTimeout(Duration.ofSeconds(10)))) {
- * for (String someValue : someCollection) {
- * ApiFuture rowFuture =
- * batcher.add(ByteString.copyFromUtf8("[ROW KEY]"));
- * rows.add(rowFuture);
- * }
- *
- * // [Optional] Sends collected elements for batching asynchronously.
- * batcher.sendOutstanding();
- *
- * // [Optional] Invokes sendOutstanding() and awaits until all pending entries are resolved.
- * batcher.flush();
- * }
- * // batcher.close() invokes `flush()` which will in turn invoke `sendOutstanding()` with await for
- * pending batches until its resolved.
- *
- * List actualRows = ApiFutures.allAsList(rows).get();
- * }
- * }