Fluo Applications

Once you have Fluo installed and running on your cluster, you can now run Fluo applications which consist of clients and observers.

For both clients and observers, you will need to include the following in your Maven pom:


Fluo provides a classpath command to help users build a runtime classpath. This command along with the hadoop jar command is useful when writing scripts to run Fluo client code. These commands allow the scripts to use the versions of Hadoop, Accumulo, and Zookeeper installed on a cluster.

Creating a Fluo client

To create a FluoClient, you will need to provide it with a FluoConfiguration object that is configured to connect to your Fluo instance.

If you have access to the fluo.properties file that was used to configure your Fluo instance, you can use it to build a FluoConfiguration object with all necessary properties which are all properties with the fluo.client.* prefix in fluo.properties:

FluoConfiguration config = new FluoConfiguration(new File("fluo.properties"));

You can also create an empty FluoConfiguration object and set properties using Java:

FluoConfiguration config = new FluoConfiguration();

Once you have FluoConfiguration object, pass it to the newClient() method of FluoFactory to create a FluoClient:

FluoClient client = FluoFactory.newClient(config)

It may help to reference the API javadocs while you are learning the Fluo API.

Running application code

The fluo exec <app name> <class> {arguments} provides an easy way to execute application code. It will execute a class with a main method if a jar containing the class is placed in the lib directory of the application. When the class is run, Fluo classes and dependencies will be on the classpath. The fluo exec command can inject the applications configuration if the class is written in the following way. Defining the injection point is optional.

import javax.inject.Inject;

public class AppCommand {

  //when run with fluo exec command, the applications configuration will be injected
  private static FluoConfiguration fluoConfig;

  public static void main(String[] args) throws Exception {
    try(FluoClient fluoClient = FluoFactory.newClient(fluoConfig)) {
      //do stuff with Fluo

Creating a Fluo observer

To create an observer, follow these steps:

  1. Create one or more classes that extend Observer like the example below. Please use slf4j for any logging in observers as slf4j supports multiple logging implementations. This is necessary as Fluo applications have a hard requirement on logback when running in YARN.

    public class InvertObserver implements Observer {
      public void process(TransactionBase tx, Bytes row, Column col) throws Exception {
        // read value
        Bytes value = tx.get(row, col);
        // invert row and value
        tx.set(value, new Column("inv", "data"), row);
  2. Create a class that implements ObserverProvider like the example below. The purpose of this class is associate a set Observers with columns that trigger the observers. The class can register multiple observers.

    class AppObserverProvider implements ObserverProvider {
      public void provide(Registry or, Context ctx) {
        //setup InvertObserver to be triggered when the column obs:data is modified
        or.forColumn(new Column("obs", "data"), NotificationType.STRONG)
          .useObserver(new InvertObserver());
        //Observer is a Functional interface.  So Observers can be written as lambdas.
        or.forColumn(new Column("new","data"), NotificationType.WEAK)
          .useObserver((tx,row,col) -> {
             Bytes combined = combineNewAndOld(tx,row);
             tx.set(row, new Column("current","data"), combined);
  3. Build a jar containing these classes and include this jar in the lib/ directory of your Fluo application.
  4. Configure your Fluo instance to use this observer provider by modifying the Observer section of fluo.properties.
  5. Initialize Fluo. During initialization Fluo will obtain the observed columns from the ObserverProvider and persist the columns in Zookeeper. These columns persisted in Zookeeper are used by transactions to know when to trigger observers.
  6. Start your Fluo instance so that your Fluo workers load the new observer.

Application Configuration

For configuring observers, fluo provides a simple mechanism to set and access application specific configuration. See the javadoc on FluoClient.getAppConfiguration() for more details.

Debugging Applications

While monitoring Fluo metrics can detect problems (like too many transaction collisions) in a Fluo application, metrics may not provide enough information to debug the root cause of the problem. To help debug Fluo applications, low-level logging of transactions can be turned on by setting the following loggers to TRACE:

Logger Level Information
fluo.tx TRACE Provides detailed information about what transactions read and wrote
fluo.tx.summary TRACE Provides a one line summary about each transaction executed
fluo.tx.collisions TRACE Provides details about what data was involved When a transaction collides with another transaction
fluo.tx.scan TRACE Provides logging for each cell read by a scan. Scan summary logged at fluo.tx level. This allows suppression of fluo.tx.scan while still seeing summary.

Below is an example log after setting fluo.tx to TRACE. The number following txid: is the transactions start timestamp from the Oracle.

2015-02-11 18:24:05,341 [fluo.tx ] TRACE: txid: 3 begin() thread: 198
2015-02-11 18:24:05,343 [fluo.tx ] TRACE: txid: 3 class: com.SimpleLoader
2015-02-11 18:24:05,357 [fluo.tx ] TRACE: txid: 3 get(4333, stat count ) -> null
2015-02-11 18:24:05,357 [fluo.tx ] TRACE: txid: 3 set(4333, stat count , 1)
2015-02-11 18:24:05,441 [fluo.tx ] TRACE: txid: 3 commit() -> SUCCESSFUL commitTs: 4
2015-02-11 18:24:05,341 [fluo.tx ] TRACE: txid: 5 begin() thread: 198
2015-02-11 18:24:05,442 [fluo.tx ] TRACE: txid: 3 close()
2015-02-11 18:24:05,343 [fluo.tx ] TRACE: txid: 5 class: com.SimpleLoader
2015-02-11 18:24:05,357 [fluo.tx ] TRACE: txid: 5 get(4333, stat count ) -> 1
2015-02-11 18:24:05,357 [fluo.tx ] TRACE: txid: 5 set(4333, stat count , 2)
2015-02-11 18:24:05,441 [fluo.tx ] TRACE: txid: 5 commit() -> SUCCESSFUL commitTs: 6
2015-02-11 18:24:05,442 [fluo.tx ] TRACE: txid: 5 close()

The log above traces the following sequence of events.

  • Transaction T1 has a start timestamp of 3
  • Thread with id 198 is executing T1, its running code from the class com.SimpleLoader
  • T1 reads row 4333 and column stat count which does not exist
  • T1 sets row 4333 and column stat count to 1
  • T1 commits successfully and its commit timestamp from the Oracle is 4.
  • Transaction T2 has a start timestamp of 5 (because its 5 > 4 it can see what T1 wrote).
  • T2 reads a value of 1 for row 4333 and column stat count
  • T2 sets row 4333 and column stat count to 2`
  • T2 commits successfully with a commit timestamp of 6

Below is an example log after only setting fluo.tx.collisions to TRACE. This setting will only log trace information when a collision occurs. Unlike the previous example, what the transaction read and wrote is not logged. This shows that a transaction with a start timestamp of 106 and a class name of com.SimpleLoader collided with another transaction on row r1 and column fam1 qual1.

2015-02-11 18:17:02,639 [tx.collisions] TRACE: txid: 106 class: com.SimpleLoader
2015-02-11 18:17:02,639 [tx.collisions] TRACE: txid: 106 collisions: {r1=[fam1 qual1 ]}

When applications read and write arbitrary binary data, this does not log so well. In order to make the trace logs human readable, non ASCII chars are escaped using hex. The convention used it \xDD where D is a hex digit. Also the \ character is escaped to make the output unambiguous.