YCSB/googlebigtable

Google Bigtable Driver for YCSB

This driver provides a YCSB workload binding for Google's hosted Bigtable, the inspiration for a number of key-value stores like HBase and Cassandra. The Bigtable Java client provides both Protobuf based GRPC and HBase client APIs. This binding implements the Protobuf API for testing the native client. To test Bigtable using the HBase API, see the hbase10 binding.

Quickstart

1. Setup a Bigtable Cluster

Login to the Google Cloud Console and follow the Creating Cluster steps. Make a note of your cluster name, zone and project ID.

2. Launch the Bigtable Shell

From the Cloud Console, launch a shell and follow the Quickstart up to step 4 where you launch the HBase shell.

3. Create a Table

For best results, use the pre-splitting strategy recommended in HBASE-4163:

hbase(main):001:0> n_splits = 200 # HBase recommends (10 * number of regionservers)
hbase(main):002:0> create 'usertable', 'cf', {SPLITS => (1..n_splits).map {|i| "user#{1000+i*(9999-1000)/n_splits}"}}

Make a note of the column family, in this example it's `cf``.

4. Fetch the Proper ALPN Boot Jar

The Bigtable protocol uses HTTP/2 which requires an ALPN protocol negotiation implementation. On JVM instantiation the implementation must be loaded before attempting to connect to the cluster. If you're using Java 7 or 8, use this Jetty Version Table to determine the version appropriate for your JVM. (ALPN is included in JDK 9+). Download the proper jar from Maven somewhere on your system.

5. Download JSON Credentials

Follow these instructions for Generating a JSON key and save it to your host.

6. Load a Workload

Switch to the root of the YCSB repo and choose the workload you want to run and load it first. With the CLI you must provide the column family, cluster properties and the ALPN jar to load.

bin/ycsb load googlebigtable -p columnfamily=cf -p google.bigtable.project.id=<PROJECT_ID> -p google.bigtable.cluster.name=<CLUSTER> -p google.bigtable.zone.name=<ZONE> -p google.bigtable.auth.service.account.enable=true -p google.bigtable.auth.json.keyfile=<PATH_TO_JSON_KEY> -jvm-args='-Xbootclasspath/p:<PATH_TO_ALPN_JAR>' -P workloads/workloada

Make sure to replace the variables in the angle brackets above with the proper value from your cluster. Additional configuration parameters are available below.

The load step only executes inserts into the datastore. After loading data, run the same workload to mix reads with writes.

bin/ycsb run googlebigtable -p columnfamily=cf -p google.bigtable.project.id=<PROJECT_ID> -p google.bigtable.cluster.name=<CLUSTER> -p google.bigtable.zone.name=<ZONE> -p google.bigtable.auth.service.account.enable=true -p google.bigtable.auth.json.keyfile=<PATH_TO_JSON_KEY> -jvm-args='-Xbootclasspath/p:<PATH_TO_ALPN_JAR>' -P workloads/workloada

Configuration Options

The following options can be configured using CLI (using the -p parameter) or hbase-site.xml (add the HBase config directory to YCSB's class path via CLI). Check the Cloud Bigtable Client project for additional tuning parameters.

• columnfamily: (Required) The Bigtable column family to target.
• google.bigtable.project.id: (Required) The ID of a Bigtable project.
• google.bigtable.cluster.name: (Required) The name of a Bigtable cluster.
• google.bigtable.zone.name: (Required) Zone where the Bigtable cluster is running.
• google.bigtable.auth.service.account.enable: Whether or not to authenticate with a service account. The default is true.
• google.bigtable.auth.json.keyfile: (Required) A service account key for authentication.
• debug: If true, prints debug information to standard out. The default is false.
• clientbuffering: Whether or not to use client side buffering and batching of write operations. This can significantly improve performance and defaults to true.