public class BigtableIO
extends java.lang.Object
Transforms
for reading from and writing to Google Cloud Bigtable.
Please note the Cloud BigTable HBase connector available here. We recommend using that connector over this one if HBase API> works for your needs.
For more information about Cloud Bigtable, see the online documentation at Google Cloud Bigtable.
The Bigtable source returns a set of rows from a single table, returning a PCollection<Row>
.
To configure a Cloud Bigtable source, you must supply a table id, a project id, an instance id
and optionally a BigtableOptions
to provide more specific connection configuration. By
default, BigtableIO.Read
will read all rows in the table. The row ranges to be read can
optionally be restricted using BigtableIO.Read.withKeyRanges(org.apache.beam.sdk.options.ValueProvider<java.util.List<org.apache.beam.sdk.io.range.ByteKeyRange>>)
, and a RowFilter
can
be specified using BigtableIO.Read.withRowFilter(org.apache.beam.sdk.options.ValueProvider<com.google.bigtable.v2.RowFilter>)
. For example:
Pipeline p = ...;
// Scan the entire table.
p.apply("read",
BigtableIO.read()
.withProjectId(projectId)
.withInstanceId(instanceId)
.withTableId("table"));
// Scan a prefix of the table.
ByteKeyRange keyRange = ...;
p.apply("read",
BigtableIO.read()
.withProjectId(projectId)
.withInstanceId(instanceId)
.withTableId("table")
.withKeyRange(keyRange));
// Scan a subset of rows that match the specified row filter.
p.apply("filtered read",
BigtableIO.read()
.withProjectId(projectId)
.withInstanceId(instanceId)
.withTableId("table")
.withRowFilter(filter));
// Configure timeouts for reads.
// Let each attempt run for 1 second, retry if the attempt failed.
// Give up after the request is retried for 60 seconds.
Duration attemptTimeout = Duration.millis(1000);
Duration operationTimeout = Duration.millis(60 * 1000);
p.apply("read",
BigtableIO.read()
.withProjectId(projectId)
.withInstanceId(instanceId)
.withTableId("table")
.withKeyRange(keyRange)
.withAttemptTimeout(attemptTimeout)
.withOperationTimeout(operationTimeout);
The Bigtable sink executes a set of row mutations on a single table. It takes as input a
PCollection<KV<ByteString, Iterable<Mutation>>>
, where the
ByteString
is the key of the row being mutated, and each Mutation
represents an
idempotent transformation to that row.
To configure a Cloud Bigtable sink, you must supply a table id, a project id, an instance id
and optionally a configuration function for BigtableOptions
to provide more specific
connection configuration, for example:
PCollection<KV<ByteString, Iterable<Mutation>>> data = ...;
data.apply("write",
BigtableIO.write()
.withProjectId("project")
.withInstanceId("instance")
.withTableId("table"));
// Configure batch size for writes
data.apply("write",
BigtableIO.write()
.withProjectId("project")
.withInstanceId("instance")
.withTableId("table")
.withBatchElements(100)); // every batch will have 100 elements
}
Optionally, BigtableIO.write() may be configured to emit BigtableWriteResult
elements
after each group of inputs is written to Bigtable. These can be used to then trigger user code
after writes have completed. See Wait
for details on the
windowing requirements of the signal and input PCollections.
// See Wait.on
PCollection<KV<ByteString, Iterable<Mutation>>> data = ...;
PCollection<BigtableWriteResult> writeResults =
data.apply("write",
BigtableIO.write()
.withProjectId("project")
.withInstanceId("instance")
.withTableId("table"))
.withWriteResults();
// The windowing of `moreData` must be compatible with `data`, see {@link org.apache.beam.sdk.transforms.Wait#on}
// for details.
PCollection<...> moreData = ...;
moreData
.apply("wait for writes", Wait.on(writeResults))
.apply("do something", ParDo.of(...))
Cloud Bigtable change streams enable users to capture and stream out mutations from their Cloud Bigtable tables in real-time. Cloud Bigtable change streams enable many use cases including integrating with a user's data analytics pipelines, support audit and archival requirements as well as triggering downstream application logic on specific database changes.
Change stream connector creates and manages a metadata table to manage the state of the
connector. By default, the table is created in the same instance as the table being streamed.
However, it can be overridden with BigtableIO.ReadChangeStream.withMetadataTableProjectId(java.lang.String)
, BigtableIO.ReadChangeStream.withMetadataTableInstanceId(java.lang.String)
, BigtableIO.ReadChangeStream.withMetadataTableTableId(java.lang.String)
, and BigtableIO.ReadChangeStream.withMetadataTableAppProfileId(java.lang.String)
. The app profile for the metadata
table must be a single cluster app profile with single row transaction enabled.
Note - To prevent unforeseen stream stalls, the BigtableIO connector outputs all data with an output timestamp of zero, making all data late, which will ensure that the stream will not stall. However, it means that you may have to deal with all data as late data, and features that depend on watermarks will not function. This means that Windowing functions and States and Timers are no longer effectively usable. Example use cases that are not possible because of this include:
Pipeline pipeline = ...;
pipeline
.apply(
BigtableIO.readChangeStream()
.withProjectId(projectId)
.withInstanceId(instanceId)
.withTableId(tableId)
.withAppProfileId(appProfileId)
.withStartTime(startTime));
Client side metrics can be enabled with an experiments flag when you run the pipeline: --experiments=bigtable_enable_client_side_metrics. These metrics can provide additional insights to your job. You can read more about client side metrics in this documentation: https://cloud.google.com/bigtable/docs/client-side-metrics.
Permission requirements depend on the PipelineRunner
that is used to execute the
pipeline. Please refer to the documentation of corresponding PipelineRunners
for more details.
Modifier and Type | Class and Description |
---|---|
static class |
BigtableIO.ExistingPipelineOptions
Overwrite options to determine what to do if change stream name is being reused and there
exists metadata of the same change stream name.
|
static class |
BigtableIO.Read
A
PTransform that reads from Google Cloud Bigtable. |
static class |
BigtableIO.ReadChangeStream |
static class |
BigtableIO.Write
A
PTransform that writes to Google Cloud Bigtable. |
static class |
BigtableIO.WriteWithResults
A
PTransform that writes to Google Cloud Bigtable and emits a BigtableWriteResult for each batch written. |
Modifier and Type | Method and Description |
---|---|
static BigtableIO.Read |
read()
Creates an uninitialized
BigtableIO.Read . |
static BigtableIO.ReadChangeStream |
readChangeStream()
Creates an uninitialized
BigtableIO.ReadChangeStream . |
static BigtableIO.Write |
write()
Creates an uninitialized
BigtableIO.Write . |
public static BigtableIO.Read read()
BigtableIO.Read
. Before use, the Read
must be
initialized with a BigtableIO.Read.withInstanceId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
and BigtableIO.Read.withProjectId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
that specifies the source Cloud Bigtable instance, and a BigtableIO.Read.withTableId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
that specifies which table to read. A RowFilter
may also
optionally be specified using BigtableIO.Read.withRowFilter(RowFilter)
.public static BigtableIO.Write write()
BigtableIO.Write
. Before use, the Write
must be
initialized with a BigtableIO.Write.withProjectId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
and BigtableIO.Write.withInstanceId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
that specifies the destination Cloud Bigtable instance, and a
BigtableIO.Write.withTableId(org.apache.beam.sdk.options.ValueProvider<java.lang.String>)
that specifies which table to write.public static BigtableIO.ReadChangeStream readChangeStream()
BigtableIO.ReadChangeStream
. Before use, the ReadChangeStream
must be initialized with
BigtableIO.ReadChangeStream.withProjectId(java.lang.String)
BigtableIO.ReadChangeStream.withInstanceId(java.lang.String)
BigtableIO.ReadChangeStream.withTableId(java.lang.String)
BigtableIO.ReadChangeStream.withAppProfileId(java.lang.String)
And optionally with
BigtableIO.ReadChangeStream.withStartTime(org.joda.time.Instant)
which defaults to now.
BigtableIO.ReadChangeStream.withHeartbeatDuration(org.joda.time.Duration)
with defaults to 1 seconds.
BigtableIO.ReadChangeStream.withMetadataTableProjectId(java.lang.String)
which defaults to value
from BigtableIO.ReadChangeStream.withProjectId(java.lang.String)
BigtableIO.ReadChangeStream.withMetadataTableInstanceId(java.lang.String)
which defaults to value
from BigtableIO.ReadChangeStream.withInstanceId(java.lang.String)
BigtableIO.ReadChangeStream.withMetadataTableTableId(java.lang.String)
which defaults to MetadataTableAdminDao.DEFAULT_METADATA_TABLE_NAME
BigtableIO.ReadChangeStream.withMetadataTableAppProfileId(java.lang.String)
which defaults to value
from BigtableIO.ReadChangeStream.withAppProfileId(java.lang.String)
BigtableIO.ReadChangeStream.withChangeStreamName(java.lang.String)
which defaults to randomly
generated string.