Flume 1.2.0 User Guide

Introduction

Overview

Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store.

Apache Flume is a top level project at the Apache Software Foundation. There are currently two release code lines available, versions 0.9.x and 1.x. This documentation applies to the 1.x codeline. Please click here for the Flume 0.9.x User Guide.

System Requirements

TBD

Architecture

Data flow model

A Flume event is defined as a unit of data flow having a byte payload and an optional set of string attributes. A Flume agent is a (JVM) process that hosts the components through which events flow from an external source to the next destination (hop).

Agent component diagram

A Flume source consumes events delivered to it by an external source like a web server. The external source sends events to Flume in a format that is recognized by the target Flume source. For example, an Avro Flume source can be used to receive Avro events from Avro clients or other Flume agents in the flow that send events from an Avro sink. When a Flume source receives an event, it stores it into one or more channels. The channel is a passive store that keeps the event until it’s consumed by a Flume sink. The JDBC channel is one example – it uses a filesystem backed embedded database. The sink removes the event from the channel and puts it into an external repository like HDFS (via Flume HDFS sink) or forwards it to the Flume source of the next Flume agent (next hop) in the flow. The source and sink within the given agent run asynchronously with the events staged in the channel.

Complex flows

Flume allows a user to build multi-hop flows where events travel through multiple agents before reaching the final destination. It also allows fan-in and fan-out flows, contextual routing and backup routes (fail-over) for failed hops.

Reliability

The events are staged in a channel on each agent. The events are then delivered to the next agent or terminal repository (like HDFS) in the flow. The events are removed from a channel only after they are stored in the channel of next agent or in the terminal repository. This is a how the single-hop message delivery semantics in Flume provide end-to-end reliability of the flow.

Flume uses a transactional approach to guarantee the reliable delivery of the events. The sources and sinks encapsulate in a transaction the storage/retrieval, respectively, of the events placed in or provided by a transaction provided by the channel. This ensures that the set of events are reliably passed from point to point in the flow. In the case of a multi-hop flow, the sink from the previous hop and the source from the next hop both have their transactions running to ensure that the data is safely stored in the channel of the next hop.

Recoverability

The events are staged in the channel, which manages recovery from failure. Flume supports a durable JDBC channel which is backed by a relational database. There’s also a memory channel which simply stores the events in an in-memory queue, which is faster but any events still left in the memory channel when an agent process dies can’t be recovered.

Setup

Setting up an agent

Flume agent configuration is stored in a local configuration file. This is a text file which has a format follows the Java properties file format. Configurations for one or more agents can be specified in the same configuration file. The configuration file includes properties of each source, sink and channel in an agent and how they are wired together to form data flows.

Configuring individual components

Each component (source, sink or channel) in the flow has a name, type, and set of properties that are specific to the type and instantiation. For example, an Avro source needs a hostname (or IP address) and a port number to receive data from. A memory channel can have max queue size (“capacity”), and an HDFS sink needs to know the file system URI, path to create files, frequency of file rotation (“hdfs.rollInterval”) etc. All such attributes of a component needs to be set in the properties file of the hosting Flume agent.

Wiring the pieces together

The agent needs to know what individual components to load and how they are connected in order to constitute the flow. This is done by listing the names of each of the sources, sinks and channels in the agent, and then specifying the connecting channel for each sink and source. For example, a agent flows events from an Avro source called avroWeb to HDFS sink hdfs-cluster1 via a JDBC channel called jdbc-channel. The configuration file will contain names of these components and jdbc-channel as a shared channel for both avroWeb source and hdfs-cluster1 sink.

Starting an agent

An agent is started using a shell script called flume-ng which is located in the bin directory of the Flume distribution. You need to specify the agent name, the config directory, and the config file on the command line:

$ bin/flume-ng agent -n $agent_name -c conf -f conf/flume-conf.properties.template

Now the agent will start running source and sinks configured in the given properties file.

A simple example

Here, we give an example configuration file, describing a single-node Flume deployment. This configuration lets a user generate events and subsequently logs them to the console.

# example.conf: A single-node Flume configuration

# Name the components on this agent
agent1.sources = source1
agent1.sinks = sink1
agent1.channels = channel1

# Describe/configure source1
agent1.sources.source1.type = netcat
agent1.sources.source1.bind = localhost
agent1.sources.source1.port = 44444

# Describe sink1
agent1.sinks.sink1.type = logger

# Use a channel which buffers events in memory
agent1.channels.channel1.type = memory
agent1.channels.channel1.capacity = 1000
agent1.channels.channel1.transactionCapactiy = 100

# Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1

This configuration defines a single agent, called agent1. agent1 has a source that listens for data on port 44444, a channel that buffers event data in memory, and a sink that logs event data to the console. The configuration file names the various components, then describes their types and configuration parameters. A given configuration file might define several named agents; when a given Flume process is launched a flag is passed telling it which named agent to manifest.

Given this configuration file, we can start Flume as follows:

$ bin/flume-ng agent --conf-file example.conf --name agent1 -Dflume.root.logger=INFO,console

Note that in a full deployment we would typically include one more option: --conf=<conf-dir>. The <conf-dir> directory would include a shell script flume-env.sh and potentially a log4j properties file. In this example, we pass a Java option to force Flume to log to the console and we go without a custom environment script.

From a separate terminal, we can then telnet port 44444 and send Flume an event:

$ telnet localhost 44444
Trying 127.0.0.1...
Connected to localhost.localdomain (127.0.0.1).
Escape character is '^]'.
Hello world! <ENTER>
OK

The original Flume terminal will output the event in a log message.

12/06/19 15:32:19 INFO source.NetcatSource: Source starting
12/06/19 15:32:19 INFO source.NetcatSource: Created serverSocket:sun.nio.ch.ServerSocketChannelImpl[/127.0.0.1:44444]
12/06/19 15:32:34 INFO sink.LoggerSink: Event: { headers:{} body: 48 65 6C 6C 6F 20 77 6F 72 6C 64 21 0D          Hello world!. }

Congratulations - you’ve successfully configured and deployed a Flume agent! Subsequent sections cover agent configuration in much more detail.

Data ingestion

Flume supports a number of mechanisms to ingest data from external sources.

RPC

An Avro client included in the Flume distribution can send a given file to Flume Avro source using avro RPC mechanism:

$ bin/flume-ng avro-client -H localhost -p 41414 -F /usr/logs/log.10

The above command will send the contents of /usr/logs/log.10 to to the Flume source listening on that ports.

Executing commands

There’s an exec source that executes a given command and consumes the output. A single ‘line’ of output ie. text followed by carriage return (‘\r’) or line feed (‘\n’) or both together.

Note

Flume does not support tail as a source. One can wrap the tail command in an exec source to stream the file.

Network streams

Flume supports the following mechanisms to read data from popular log stream types, such as:

  1. Avro
  2. Syslog
  3. Netcat

Setting multi-agent flow

Two agents communicating over Avro RPC

In order to flow the data across multiple agents or hops, the sink of the previous agent and source of the current hop need to be avro type with the sink pointing to the hostname (or IP address) and port of the source.

Consolidation

A very common scenario in log collection is a large number of log producing clients sending data to a few consumer agents that are attached to the storage subsystem. For examples, logs collected from hundreds of web servers sent to a dozen of agents that write to HDFS cluster.

A fan-in flow using Avro RPC to consolidate events in one place

This can be achieved in Flume by configuring a number of first tier agents with an avro sink, all pointing to an avro source of single agent. This source on the second tier agent consolidates the received events into a single channel which is consumed by a sink to its final destination.

Multiplexing the flow

Flume supports multiplexing the event flow to one or more destinations. This is achieved by defining a flow multiplexer that can replicate or selectively route an event to one or more channels.

A fan-out flow using a (multiplexing) channel selector

The above example shows a source from agent “foo” fanning out the flow to three different channels. This fan out can be replicating or multiplexing. In case of replicating flow, each event is sent to all three channels. For the multiplexing case, an event is delivered to a subset of available channels when an event’s attribute matches a preconfigured value. For example, if an event attribute called “txnType” is set to “customer”, then it should go to channel1 and channel3, if it’s “vendor” then it should go to channel2, otherwise channel3. The mapping can be set in the agent’s configuration file.

Configuration

As mentioned in the earlier section, Flume agent configuration is read from a file that resembles a Java property file format with hierarchical property settings.

Defining the flow

To define the flow within a single agent, you need to link the sources and sinks via a channel. You need to list the sources, sinks and channels for the given agent, and then point the source and sink to a channel. A source instance can specify multiple channels, but a sink instance can only specify on channel. The format is as follows:

# list the sources, sinks and channels for the agent
<Agent>.sources = <Source>
<Agent>.sinks = <Sink>
<Agent>.channels = <Channel1> <Channel2>

# set channel for source
<Agent>.sources.<Source>.channels = <Channel1> <Channel2> ...

# set channel for sink
<Agent>.sinks.<Sink>.channel = <Channel1>

For example an agent named agent_foo is reading data from an external avro client and sending it to HDFS via a memory channel. The config file weblog.config could look like:

# list the sources, sinks and channels for the agent
agent_foo.sources = avro-appserver-src-1
agent_foo.sinks = hdfs-sink-1
agent_foo.channels = mem-channel-1

# set channel for source
agent_foo.sources.avro-appserver-src-1.channels = mem-channel-1

# set channel for sink
agent_foo.sinks.hdfs-sink-1.channel = mem-channel-1

This will make the events flow from avro-AppSrv-source to hdfs-Cluster1-sink through the memory channel mem-channel-1. When the agent is started with the weblog.config as its config file, it will instantiate that flow.

Configuring individual components

After defining the flow, you need to set properties of each source, sink and channel. This is done in the same hierarchical namespace fashion where you set the component type and other values for the properties specific to each component:

# properties for sources
<Agent>.sources.<Source>.<someProperty> = <someValue>

# properties for channels
<Agent>.channel.<Channel>.<someProperty> = <someValue>

# properties for sinks
<Agent>.sources.<Sink>.<someProperty> = <someValue>

The property “type” needs to be set for each component for Flume to understand what kind of object it needs to be. Each source, sink and channel type has its own set of properties required for it to function as intended. All those need to be set as needed. In the previous example, we have a flow from avro-AppSrv-source to hdfs-Cluster1-sink through the memory channel mem-channel-1. Here’s an example that shows configuration of each of those components:

agent_foo.sources = avro-AppSrv-source
agent_foo.sinks = hdfs-Cluster1-sink
agent_foo.channels = mem-channel-1

# set channel for sources, sinks

# properties of avro-AppSrv-source
agent_foo.sources.avro-AppSrv-source.type = avro
agent_foo.sources.avro-AppSrv-source.bind = localhost
agent_foo.sources.avro-AppSrv-source.port = 10000

# properties of mem-channel-1
agent_foo.channels.mem-channel-1.type = memory
agent_foo.channels.mem-channel-1.capacity = 1000
agent_foo.channels.mem-channel-1.transactionCapacity = 100

# properties of hdfs-Cluster1-sink
agent_foo.sinks.hdfs-Cluster1-sink.type = hdfs
agent_foo.sinks.hdfs-Cluster1-sink.hdfs.path = hdfs://namenode/flume/webdata

#...

Adding multiple flows in an agent

A single Flume agent can contain several independent flows. You can list multiple sources, sinks and channels in a config. These components can be linked to form multiple flows:

# list the sources, sinks and channels for the agent
<Agent>.sources = <Source1> <Source2>
<Agent>.sinks = <Sink1> <Sink2>
<Agent>.channels = <Channel1> <Channel2>

Then you can link the sources and sinks to their corresponding channels (for sources) of channel (for sinks) to setup two different flows. For example, if you need to setup two flows in an agent, one going from an external avro client to external HDFS and another from output of a tail to avro sink, then here’s a config to do that:

# list the sources, sinks and channels in the agent
agent_foo.sources = avro-AppSrv-source1 exec-tail-source2
agent_foo.sinks = hdfs-Cluster1-sink1 avro-forward-sink2
agent_foo.channels = mem-channel-1 jdbc-channel-2

# flow #1 configuration
agent_foo.sources.avro-AppSrv-source1.channels = mem-channel-1
agent_foo.sinks.hdfs-Cluster1-sink1.channel = mem-channel-1

# flow #2 configuration
agent_foo.sources.exec-tail-source2.channels = jdbc-channel-2
agent_foo.sinks.avro-forward-sink2.channel = jdbc-channel-2

Configuring a multi agent flow

To setup a multi-tier flow, you need to have an avro sink of first hop pointing to avro source of the next hop. This will result in the first Flume agent forwarding events to the next Flume agent. For example, if you are periodically sending files (1 file per event) using avro client to a local Flume agent, then this local agent can forward it to another agent that has the mounted for storage.

Weblog agent config:

# list sources, sinks and channels in the agent
agent_foo.sources = avro-AppSrv-source
agent_foo.sinks = avro-forward-sink
agent_foo.channels = jdbc-channel

# define the flow
agent_foo.sources.avro-AppSrv-source.channels = jdbc-channel
agent_foo.sinks.avro-forward-sink.channel = jdbc-channel

# avro sink properties
agent_foo.sources.avro-forward-sink.type = avro
agent_foo.sources.avro-forward-sink.hostname = 10.1.1.100
agent_foo.sources.avro-forward-sink.port = 10000

# configure other pieces
#...

HDFS agent config:

# list sources, sinks and channels in the agent
agent_foo.sources = avro-collection-source
agent_foo.sinks = hdfs-sink
agent_foo.channels = mem-channel

# define the flow
agent_foo.sources.avro-collection-source.channels = mem-channel
agent_foo.sinks.hdfs-sink.channel = mem-channel

# avro sink properties
agent_foo.sources.avro-collection-source.type = avro
agent_foo.sources.avro-collection-source.bind = 10.1.1.100
agent_foo.sources.avro-collection-source.port = 10000

# configure other pieces
#...

Here we link the avro-forward-sink from the weblog agent to the avro-collection-source of the hdfs agent. This will result in the events coming from the external appserver source eventually getting stored in HDFS.

Fan out flow

As discussed in previous section, Flume support fanning out the flow from one source to multiple channels. There are two modes of fan out, replicating and multiplexing. In the replicating flow the event is sent to all the configured channels. In case of multiplexing, the event is sent to only a subset of qualifying channels. To fan out the flow, one needs to specify a list of channels for a source and the policy for the fanning it out. This is done by adding a channel “selector” that can be replicating or multiplexing. Then further specify the selection rules if it’s a multiplexer. If you don’t specify an selector, then by default it’s replicating:

# List the sources, sinks and channels for the agent
<Agent>.sources = <Source1>
<Agent>.sinks = <Sink1> <Sink2>
<Agent>.channels = <Channel1> <Channel2>

# set list of channels for source (separated by space)
<Agent>.sources.<Source1>.channels = <Channel1> <Channel2>

# set channel for sinks
<Agent>.sinks.<Sink1>.channel = <Channel1>
<Agent>.sinks.<Sink2>.channel = <Channel2>

<Agent>.sources.<Source1>.selector.type = replicating

The multiplexing select has a further set of properties to bifurcate the flow. This requires specifying a mapping of an event attribute to a set for channel. The selector checks for each configured attribute in the event header. If it matches the specified value, then that event is sent to all the channels mapped to that value. If there’s no match, then the event is sent to set of channels configured as default:

# Mapping for multiplexing selector
<Agent>.sources.<Source1>.selector.type = multiplexing
<Agent>.sources.<Source1>.selector.header = <someHeader>
<Agent>.sources.<Source1>.selector.mapping.<Value1> = <Channel1>
<Agent>.sources.<Source1>.selector.mapping.<Value2> = <Channel1> <Channel2>
<Agent>.sources.<Source1>.selector.mapping.<Value3> = <Channel2>
#...

<Agent>.sources.<Source1>.selector.default = <Channel2>

The mapping allows overlapping the channels for each value. The default must be set for a multiplexing select which can also contain any number of channels.

The following example has a single flow that multiplexed to two paths. The agent named agent_foo has a single avro source and two channels linked to two sinks:

# list the sources, sinks and channels in the agent
agent_foo.sources = avro-AppSrv-source1
agent_foo.sinks = hdfs-Cluster1-sink1 avro-forward-sink2
agent_foo.channels = mem-channel-1 jdbc-channel-2

# set channels for source
agent_foo.sources.avro-AppSrv-source1.channels = mem-channel-1 jdbc-channel-2

# set channel for sinks
agent_foo.sinks.hdfs-Cluster1-sink1.channel = mem-channel-1
agent_foo.sinks.avro-forward-sink2.channel = jdbc-channel-2

# channel selector configuration
agent_foo.sources.avro-AppSrv-source1.selector.type = multiplexing
agent_foo.sources.avro-AppSrv-source1.selector.header = State
agent_foo.sources.avro-AppSrv-source1.selector.mapping.CA = mem-channel-1
agent_foo.sources.avro-AppSrv-source1.selector.mapping.AZ = jdbc-channel-2
agent_foo.sources.avro-AppSrv-source1.selector.mapping.NY = mem-channel-1 jdbc-channel-2
agent_foo.sources.avro-AppSrv-source1.selector.default = mem-channel-1

The selector checks for a header called “State”. If the value is “CA” then its sent to mem-channel-1, if its “AZ” then it goes to jdbc-channel-2 or if its “NY” then both. If the “State” header is not set or doesn’t match any of the three, then it goes to mem-channel-1 which is designated as ‘default’.

Flume Sources

Avro Source

Listens on Avro port and receives events from external Avro client streams. When paired with the built-in AvroSink on another (previous hop) Flume agent, it can create tiered collection topologies. Required properties are in bold.

Property Name Default Description
channels  
type The component type name, needs to be avro
bind hostname or IP address to listen on
port Port # to bind to
threads Maximum number of worker threads to spawn
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = avrosource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.avrosource-1.type = avro
agent_foo.sources.avrosource-1.channels = memoryChannel-1
agent_foo.sources.avrosource-1.bind = 0.0.0.0
agent_foo.sources.avrosource-1.port = 4141

Exec Source

Exec source runs a given Unix command on start-up and expects that process to continuously produce data on standard out (stderr is simply discarded, unless property logStdErr is set to true). If the process exits for any reason, the source also exits and will produce no further data. This means configurations such as cat [named pipe] or tail -F [file] are going to produce the desired results where as date will probably not - the former two commands produce streams of data where as the latter produces a single event and exits.

Required properties are in bold.

Property Name Default Description
channels  
type The component type name, needs to be exec
command The command to execute
restartThrottle 10000 Amount of time (in millis) to wait before attempting a restart
restart false Whether the executed cmd should be restarted if it dies
logStdErr false Whether the command’s stderr should be logged
batchSize 20 The max number of lines to read and send to the channel at a time
selector.type replicating replicating or multiplexing
selector.*   Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Warning

The problem with ExecSource and other asynchronous sources is that the source can not guarantee that if there is a failure to put the event into the Channel the client knows about it. In such cases, the data will be lost. As a for instance, one of the most commonly requested features is the tail -F [file]-like use case where an application writes to a log file on disk and Flume tails the file, sending each line as an event. While this is possible, there’s an obvious problem; what happens if the channel fills up and Flume can’t send an event? Flume has no way of indicating to the application writing the log file that it needs to retain the log or that the event hasn’t been sent, for some reason. If this doesn’t make sense, you need only know this: Your application can never guarantee data has been received when using a unidirectional asynchronous interface such as ExecSource! As an extension of this warning - and to be completely clear - there is absolutely zero guarantee of event delivery when using this source. You have been warned.

Note

You can use ExecSource to emulate TailSource from Flume 0.9x (flume og). Just use unix command tail -F /full/path/to/your/file. Parameter -F is better in this case than -f as it will also follow file rotation.

Example for agent named agent_foo:

agent_foo.sources = tailsource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.tailsource-1.type = exec
agent_foo.sources.tailsource-1.command = tail -F /var/log/secure
agent_foo.sources.tailsource-1.channels = memoryChannel-1

NetCat Source

A netcat-like source that listens on a given port and turns each line of text into an event. Acts like nc -k -l [host] [port]. In other words, it opens a specified port and listens for data. The expectation is that the supplied data is newline separated text. Each line of text is turned into a Flume event and sent via the connected channel.

Required properties are in bold.

Property Name Default Description
channels  
type The component type name, needs to be netcat
bind Host name or IP address to bind to
port Port # to bind to
max-line-length 512 Max line length per event body (in bytes)
selector.type replicating replicating or multiplexing
selector.*   Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = ncsource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.ncsource-1.type = netcat
agent_foo.sources.ncsource-1.bind = 0.0.0.0
agent_foo.sources.ncsource-1.bind = 6666
agent_foo.sources.ncsource-1.channels = memoryChannel-1

Sequence Generator Source

A simple sequence generator that continuously generates events with a counter that starts from 0 and increments by 1. Useful mainly for testing. Required properties are in bold.

Property Name Default Description
channels  
type The component type name, needs to be seq
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = ncsource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.ncsource-1.type = seq
agent_foo.sources.ncsource-1.channels = memoryChannel-1

Syslog Sources

Reads syslog data and generate Flume events. The UDP source treats an entire message as a single event. The TCP source on creates a new event for a string of characters separated by carriage return (‘n’).

Required properties are in bold.

Syslog TCP Source
Property Name Default Description
channels  
type The component type name, needs to be syslogtcp
host Host name or IP address to bind to
port Port # to bind to
eventSize 2500  
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

For example, a syslog TCP source for agent named agent_foo:

agent_foo.sources = syslogsource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.syslogsource-1.type = syslogtcp
agent_foo.sources.syslogsource-1.port = 5140
agent_foo.sources.syslogsource-1.host = localhost
agent_foo.sources.syslogsource-1.channels = memoryChannel-1
Syslog UDP Source
Property Name Default Description
channels  
type The component type name, needs to be syslogudp
host Host name or IP address to bind to
port Port # to bind to
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

For example, a syslog UDP source for agent named agent_foo:

agent_foo.sources = syslogsource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.syslogsource-1.type = syslogudp
agent_foo.sources.syslogsource-1.port = 5140
agent_foo.sources.syslogsource-1.host = localhost
agent_foo.sources.syslogsource-1.channels = memoryChannel-1

Legacy Sources

The legacy sources allow a Flume 1.x agent to receive events from Flume 0.9.4 agents. It accepts events in the Flume 0.9.4 format, converts them to the Flume 1.0 format, and stores them in the connected channel. The 0.9.4 event properties like timestamp, pri, host, nanos, etc get converted to 1.x event header attributes. The legacy source supports both Avro and Thrift RPC connections. To use this bridge between two Flume versions, you need to start a Flume 1.x agent with the avroLegacy or thriftLegacy source. The 0.9.4 agent should have the agent Sink pointing to the host/port of the 1.x agent.

Note

The reliability semantics of Flume 1.x are different from that of Flume 0.9.x. The E2E or DFO mode of a Flume 0.9.x agent will not be supported by the legacy source. The only supported 0.9.x mode is the best effort, though the reliability setting of the 1.x flow will be applicable to the events once they are saved into the Flume 1.x channel by the legacy source.

Required properties are in bold.

Avro Legacy Source
Property Name Default Description
channels  
type The component type name, needs to be org.apache.flume.source.avroLegacy.AvroLegacySource
host The hostname or IP address to bind to
port The port # to listen on
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = legacysource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.legacysource-1.type = org.apache.flume.source.avroLegacy.AvroLegacySource
agent_foo.sources.legacysource-1.host = 0.0.0.0
agent_foo.sources.legacysource-1.bind = 6666
agent_foo.sources.legacysource-1.channels = memoryChannel-1
Thrift Legacy Source
Property Name Default Description
channels  
type The component type name, needs to be org.apache.source.thriftLegacy.ThriftLegacySource
host The hostname or IP address to bind to
port The port # to listen on
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = legacysource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.legacysource-1.type = org.apache.source.thriftLegacy.ThriftLegacySource
agent_foo.sources.legacysource-1.host = 0.0.0.0
agent_foo.sources.legacysource-1.bind = 6666
agent_foo.sources.legacysource-1.channels = memoryChannel-1

Custom Source

A custom source is your own implementation of the Source interface. A custom source’s class and its dependencies must be included in the agent’s classpath when starting the Flume agent. The type of the custom source is its FQCN.

Property Name Default Description
channels  
type The component type name, needs to be your FQCN
selector.type   replicating or multiplexing
selector.* replicating Depends on the selector.type value
interceptors Space separated list of interceptors
interceptors.*    

Example for agent named agent_foo:

agent_foo.sources = legacysource-1
agent_foo.channels = memoryChannel-1
agent_foo.sources.legacysource-1.type = your.namespace.YourClass
agent_foo.sources.legacysource-1.channels = memoryChannel-1

Flume Sinks

HDFS Sink

This sink writes events into the Hadoop Distributed File System (HDFS). It currently supports creating text and sequence files. It supports compression in both file types. The files can be rolled (close current file and create a new one) periodically based on the elapsed time or size of data or number of events. It also buckets/partitions data by attributes like timestamp or machine where the event originated. The HDFS directory path may contain formatting escape sequences that will replaced by the HDFS sink to generate a directory/file name to store the events. Using this sink requires hadoop to be installed so that Flume can use the Hadoop jars to communicate with the HDFS cluster. Note that a version of Hadoop that supports the sync() call is required.

The following are the escape sequences supported:

Alias Description
%{host} Substitute value of event header named “host”. Arbitrary header names are supported.
%t Unix time in milliseconds
%a locale’s short weekday name (Mon, Tue, ...)
%A locale’s full weekday name (Monday, Tuesday, ...)
%b locale’s short month name (Jan, Feb, ...)
%B locale’s long month name (January, February, ...)
%c locale’s date and time (Thu Mar 3 23:05:25 2005)
%d day of month (01)
%D date; same as %m/%d/%y
%H hour (00..23)
%I hour (01..12)
%j day of year (001..366)
%k hour ( 0..23)
%m month (01..12)
%M minute (00..59)
%p locale’s equivalent of am or pm
%s seconds since 1970-01-01 00:00:00 UTC
%S second (00..59)
%y last two digits of year (00..99)
%Y year (2010)
%z +hhmm numeric timezone (for example, -0400)

The file in use will have the name mangled to include ”.tmp” at the end. Once the file is closed, this extension is removed. This allows excluding partially complete files in the directory. Required properties are in bold.

Note

For all of the time related escape sequences, a header with the key “timestamp” must exist among the headers of the event. One way to add this automatically is to use the TimestampInterceptor.

Name Default Description
channel  
type The component type name, needs to be hdfs
hdfs.path HDFS directory path (eg hdfs://namenode/flume/webdata/)
hdfs.filePrefix FlumeData Name prefixed to files created by Flume in hdfs directory
hdfs.rollInterval 30 Number of seconds to wait before rolling current file (0 = never roll based on time interval)
hdfs.rollSize 1024 File size to trigger roll, in bytes (0: never roll based on file size)
hdfs.rollCount 10 Number of events written to file before it rolled (0 = never roll based on number of events)
hdfs.batchSize 1 number of events written to file before it flushed to HDFS
hdfs.txnEventMax 100  
hdfs.codeC Compression codec. one of following : gzip, bzip2, lzo, snappy
hdfs.fileType SequenceFile File format: currently SequenceFile, DataStream or CompressedStream (1)DataStream will not compress output file and please don’t set codeC (2)CompressedStream requires set hdfs.codeC with an available codeC
hdfs.maxOpenFiles 5000  
hdfs.writeFormat “Text” or “Writable”
hdfs.appendTimeout 1000  
hdfs.callTimeout 10000  
hdfs.threadsPoolSize 10 Number of threads per HDFS sink for HDFS IO ops (open, write, etc.)
hdfs.rollTimerPoolSize 1 Number of threads per HDFS sink for scheduling timed file rolling
hdfs.kerberosPrincipal Kerberos user principal for accessing secure HDFS
hdfs.kerberosKeytab Kerberos keytab for accessing secure HDFS
hdfs.round false Should the timestamp be rounded down (if true, affects all time based escape sequences except %t)
hdfs.roundValue 1 Rounded down to the highest multiple of this (in the unit configured using hdfs.roundUnit), less than current time.
hdfs.roundUnit second The unit of the round down value - second, minute or hour.
serializer TEXT Other possible options include AVRO_EVENT or the fully-qualified class name of an implementation of the EventSerializer.Builder interface.
serializer.*    

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = hdfsSink-1
agent_foo.sinks.hdfsSink-1.type = hdfs
agent_foo.sinks.hdfsSink-1.channels = memoryChannel-1
agent_foo.sinks.hdfsSink-1.hdfs.path = /flume/events/%y-%m-%d/%H%M/%S
agent_foo.sinks.hdfsSink-1.hdfs.filePrefix = events-
agent_foo.sinks.hdfsSink-1.hdfs.round = true
agent_foo.sinks.hdfsSink-1.hdfs.roundValue = 10
agent_foo.sinks.hdfsSink-1.hdfs.roundUnit = minute

The above configuration will round down the timestamp to the last 10th minute. For example, an event with timestamp 11:54:34 AM, June 12, 2012 will cause the hdfs path to become /flume/events/2012-06-12/1150/00.

Logger Sink

Logs event at INFO level. Typically useful for testing/debugging purpose. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be logger

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = loggerSink-1
agent_foo.sinks.loggerSink-1.type = logger
agent_foo.sinks.loggerSink-1.channels = memoryChannel-1

Avro Sink

This sink forms one half of Flume’s tiered collection support. Flume events sent to this sink are turned into Avro events and sent to the configured hostname / port pair. The events are taken from the configured Channel in batches of the configured batch size. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be avro.
hostname The hostname or IP address to bind to.
port The port # to listen on.
batch-size 100 number of event to batch together for send.
connect-timeout 20000 Amount of time (ms) to allow for the first (handshake) request.
request-timeout 20000 Amount of time (ms) to allow for requests after the first.

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = avroSink-1
agent_foo.sinks.avroSink-1.type = avro
agent_foo.sinks.avroSink-1.channels = memoryChannel-1
agent_foo.sinks.avroSink-1.hostname = 10.10.10.10
agent_foo.sinks.avroSink-1.port = 4545

IRC Sink

The IRC sink takes messages from attached channel and relays those to configured IRC destinations. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be irc
hostname The hostname or IP address to connect to
port 6667 The port number of remote host to connect
nick Nick name
user User name
password User password
chan channel
name    
splitlines (boolean)
splitchars n line separator (if you were to enter the default value into the config file, then you would need to escape the backslash, like this: “\n”)

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = ircSink-1
agent_foo.sinks.ircSink-1.type = irc
agent_foo.sinks.ircSink-1.channels = memoryChannel-1
agent_foo.sinks.ircSink-1.hostname = irc.yourdomain.com
agent_foo.sinks.ircSink-1.nick = flume
agent_foo.sinks.ircSink-1.chan = #flume

File Roll Sink

Stores events on the local filesystem. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be FILE_ROLL.
sink.directory The directory where files will be stored
sink.rollInterval 30 Roll the file every 30 seconds. Specifying 0 will disable rolling and cause all events to be written to a single file.
sink.serializer TEXT Other possible options include AVRO_EVENT or the FQCN of an implementation of EventSerializer.Builder interface.

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = fileSink-1
agent_foo.sinks.fileSink-1.type = FILE_ROLL
agent_foo.sinks.fileSink-1.channels = memoryChannel-1
agent_foo.sinks.fileSink-1.sink.directory = /var/log/flume

Null Sink

Discards all events it receives from the channel. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be NULL.

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = nullSink-1
agent_foo.sinks.nullSink-1.type = NULL
agent_foo.sinks.nullSink-1.channels = memoryChannel-1

HBaseSinks

HBaseSink

This sink writes data to HBase. The Hbase configuration is picked up from the first hbase-site.xml encountered in the classpath. A class implementing HbaseEventSerializer which is specified by the configuration is used to convert the events into HBase puts and/or increments. These puts and increments are then written to HBase. This sink provides the same consistency guarantees as HBase, which is currently row-wise atomicity. In the event of Hbase failing to write certain events, the sink will replay all events in that transaction. For convenience two serializers are provided with flume. The SimpleHbaseEventSerializer (org.apache.flume.sink.hbase.SimpleHbaseEventSerializer) writes the event body as is to HBase, and optionally increments a column in Hbase. This is primarily an example implementation. The RegexHbaseEventSerializer (org.apache.flume.sink.hbase.RegexHbaseEventSerializer) breaks the event body based on the given regex and writes each part into different columns.

The type is the FQCN: org.apache.flume.sink.hbase.HBaseSink. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be org.apache.flume.sink.HBaseSink
table The name of the table in Hbase to write to.
columnFamily The column family in Hbase to write to.
batchSize 100 Number of events to be written per txn.
serializer org.apache.flume.sink.hbase.SimpleHbaseEventSerializer  
serializer.* Properties to be passed to the serializer.

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = hbaseSink-1
agent_foo.sinks.hbaseSink-1.type = org.apache.flume.sink.hbase.HBaseSink
agent_foo.sinks.hbaseSink-1.table = foo_table
agent_foo.sinks.hbaseSink-1.columnFamily = bar_cf
agent_foo.sinks.hbaseSink-1.serializer = org.apache.flume.sink.hbase.RegexHbaseEventSerializer
agent_foo.sinks.hbaseSink-1.channels = memoryChannel-1
AsyncHBaseSink

This sink writes data to HBase using an asynchronous model. A class implementing AsyncHbaseEventSerializer which is specified by the configuration is used to convert the events into HBase puts and/or increments. These puts and increments are then written to HBase. This sink provides the same consistency guarantees as HBase, which is currently row-wise atomicity. In the event of Hbase failing to write certain events, the sink will replay all events in that transaction. This sink is still experimental. The type is the FQCN: org.apache.flume.sink.hbase.AsyncHBaseSink. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be org.apache.flume.sink.AsyncHBaseSink
table The name of the table in Hbase to write to.
columnFamily The column family in Hbase to write to.
batchSize 100 Number of events to be written per txn.
timeout The length of time (in milliseconds) the sink waits for acks from hbase for all events in a transaction. If no timeout is specified, the sink will wait forever.
serializer org.apache.flume.sink.hbase.SimpleAsyncHbaseEventSerializer  
serializer.* Properties to be passed to the serializer.

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = hbaseSink-1
agent_foo.sinks.hbaseSink-1.type = org.apache.flume.sink.hbase.AsyncHBaseSink
agent_foo.sinks.hbaseSink-1.table = foo_table
agent_foo.sinks.hbaseSink-1.columnFamily = bar_cf
agent_foo.sinks.hbaseSink-1.serializer = org.apache.flume.sink.hbase.SimpleAsyncHbaseEventSerializer
agent_foo.sinks.hbaseSink-1.channels = memoryChannel-1

Custom Sink

A custom sink is your own implementation of the Sink interface. A custom sink’s class and its dependencies must be included in the agent’s classpath when starting the Flume agent. The type of the custom sink is its FQCN. Required properties are in bold.

Property Name Default Description
channel  
type The component type name, needs to be your FQCN

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.sinks = customSink-1
agent_foo.sinks.customSink-1.type = your.namespace.YourClass
agent_foo.sinks.customSink-1.channels = memoryChannel-1

Flume Channels

Channels are the repositories where the events are staged on a agent. Source adds the events and Sink removes it.

Memory Channel

The events are stored in a an in-memory queue with configurable max size. It’s ideal for flow that needs higher throughput and prepared to lose the staged data in the event of a agent failures. Required properties are in bold.

Property Name Default Description
type The component type name, needs to be memory
capacity 100 The max number of events stored in the channel
transactionCapacity 100 The max number of events stored in the channel per transaction
keep-alive 3 Timeout in seconds for adding or removing an event

Example for agent named agent_foo:

agent_foo.channels = memoryChannel-1
agent_foo.channels.memoryChannel-1.type = memory
agent_foo.channels.memoryChannel-1.capacity = 1000

JDBC Channel

The events are stored in a persistent storage that’s backed by a database. The JDBC channel currently supports embedded Derby. This is a durable channel that’s ideal for the flows where recoverability is important. Required properties are in bold.

Property Name Default Description
type The component type name, needs to be jdbc
db.type DERBY Database vendor, needs to be DERBY.
driver.class org.apache.derby.jdbc.EmbeddedDriver Class for vendor’s JDBC driver
driver.url (constructed from other properties) JDBC connection URL
db.username “sa” User id for db connection
db.password password for db connection
connection.properties.file JDBC Connection property file path
create.schema true If true, then creates db schema if not there
create.index true Create indexes to speed up lookups
create.foreignkey true  
transaction.isolation “READ_COMMITTED” Isolation level for db session READ_UNCOMMITTED, READ_COMMITTED, SERIALIZABLE, REPEATABLE_READ
maximum.connections 10 Max connections allowed to db
maximum.capacity 0 (unlimited) Max number of events in the channel
sysprop.*   DB Vendor specific properties
sysprop.user.home   Home path to store embedded Derby database

Example for agent named agent_foo:

agent_foo.channels = jdbcChannel-1
agent_foo.channels.jdbcChannel-1.type = jdbc

Recoverable Memory Channel

Warning

The Recoverable Memory Channel has been deprecated in favor of the FileChannel. FileChannel is durable channel and performs better than the Recoverable Memory Channel.

Required properties are in bold.

Property Name Default Description
type The component type name, needs to be org.apache.flume.channel.recoverable.memory.RecoverableMemoryChannel
wal.dataDir ${user.home}/.flume/recoverable-memory-channel  
wal.rollSize (0x04000000) Max size (in bytes) of a single file before we roll
wal.minRetentionPeriod 300000 Min amount of time (in millis) to keep a log
wal.workerInterval 60000 How often (in millis) the background worker checks for old logs
wal.maxLogsSize (0x20000000) Total amt (in bytes) of logs to keep, excluding the current log

File Channel

Required properties are in bold.

Property Name Default Description
type The component type name, needs to be FILE.
checkpointDir ~/.flume/file-channel/checkpoint The directory where checkpoint file will be stored
dataDirs ~/.flume/file-channel/data The directory where log files will be stored
transactionCapacity 1000 The maximum size of transaction supported by the channel
checkpointInterval 30000 Amount of time (in millis) between checkpoints
maxFileSize 2146435071 Max size (in bytes) of a single log file
capacity 1000000 Maximum capacity of the channel
keep-alive 3 Amount of time (in sec) to wait for a put operation
write-timeout 3 Amount of time (in sec) to wait for a write operation

Note

By default the File Channel uses paths for checkpoint and data directories that are within the user home as specified above. As a result if you have more than one File Channel instances active within the agent, only one will be able to lock the directories and cause the other channel initialization to fail. It is therefore necessary that you provide explicit paths to all the configured channels, preferably on different disks. Furthermore, as file channel will sync to disk after every commit, coupling it with a sink/source that batches events together may be necessary to provide good performance where multiple disks are not available for checkpoint and data directories.

Example for agent named agent_foo:

agent_foo.channels = fileChannel-1
agent_foo.channels.fileChannel-1.type = file
agent_foo.channels.fileChannel-1.checkpointDir = /mnt/flume/checkpoint
agent_foo.channels.fileChannel-1.dataDirs = /mnt/flume/data

Pseudo Transaction Channel

Warning

The Pseudo Transaction Channel is only for unit testing purposes and is NOT meant for production use.

Required properties are in bold.

Property Name Default Description
type The component type name, needs to be org.apache.flume.channel.PseudoTxnMemoryChannel
capacity 50 The max number of events stored in the channel
keep-alive 3 Timeout in seconds for adding or removing an event

Custom Channel

A custom channel is your own implementation of the Channel interface. A custom channel’s class and its dependencies must be included in the agent’s classpath when starting the Flume agent. The type of the custom channel is its FQCN. Required properties are in bold.

Property Name Default Description
type The component type name, needs to be a fully-qualified class name

Example for agent named agent_foo:

agent_foo.channels = customChannel-1
agent_foo.channels.customChannel-1.type = your.domain.YourClass

Flume Channel Selectors

If the type is not specified, then defaults to “replicating”.

Replicating Channel Selector (default)

Required properties are in bold.

Property Name Default Description
selector.type replicating The component type name, needs to be replicating

Example for agent named agent_foo and it’s source called source_foo:

agent_foo.sources = source_foo
agent_foo.channels = channel-1 channel-2 channel-3
agent_foo.source.source_foo.selector.type = replicating
agent_foo.source.source_foo.channels = channel-1 channel-2 channel-3

Multiplexing Channel Selector

Required properties are in bold.

Property Name Default Description
selector.type replicating The component type name, needs to be multiplexing
selector.header flume.selector.header  
selector.default  
selector.mapping.*  

Example for agent named agent_foo and it’s source called source_foo:

agent_foo.sources = source_foo
agent_foo.channels = channel-1 channel-2 channel-3 channel-4
agent_foo.sources.source_foo.selector.type = multiplexing
agent_foo.sources.source_foo.selector.header = state
agent_foo.sources.source_foo.selector.mapping.CZ = channel-1
agent_foo.sources.source_foo.selector.mapping.US = channel-2 channel-3
agent_foo.sources.source_foo.selector.default = channel-4

Custom Channel Selector

A custom channel selector is your own implementation of the ChannelSelector interface. A custom channel selector’s class and its dependencies must be included in the agent’s classpath when starting the Flume agent. The type of the custom channel selector is its FQCN.

Property Name Default Description
selector.type The component type name, needs to be your FQCN

Example for agent named agent_foo and it’s source called source_foo:

agent_foo.sources = source_foo
agent_foo.channels = channel-1
agent_foo.sources.source_foo.selector.type = your.namespace.YourClass

Flume Sink Processors

Sink groups allow users to group multiple sinks into one entity. Sink processors can be used to provide load balancing capabilities over all sinks inside the group or to achieve fail over from one sink to another in case of temporal failure.

Default Sink Processor

Required properties are in bold.

Property Name Default Description
processor.sinks Space separated list of sinks that are participating in the group
processor.type default The component type name, needs to be default, failover or load_balance

Example for agent named agent_foo:

agent_foo.sinkgroups = group1
agent_foo.sinkgroups.group1.sinks = sink1 sink2
agent_foo.sinkgroups.group1.processor.type = load_balance

Default Sink Processor

Default sink processor accepts only a single sink. User is not forced to create processor (sink group) for single sinks. Instead user can follow the source - channel - sink pattern that was explained above in this user guide.

Example for agent named agent_foo:

agent_foo.sinkgroups = group1
agent_foo.sinkgroups.group1.sinks = sink1 sink2
agent_foo.sinkgroups.group1.processor.type = load_balance

Default Sink Processor

Default sink processor accepts only a single sink. User is not forced to create processor (sink group) for single sinks. Instead user can follow the source - channel - sink pattern that was explained above in this user guide.

Failover Sink Processor

Failover Sink Processor maintains a prioritized list of sinks, guaranteeing that so long as one is available events will be processed (delivered).

The fail over mechanism works by relegating failed sinks to a pool where they are assigned a cool down period, increasing with sequential failures before they are retried. Once a sink successfully sends an event it is restored to the live pool.

To configure, set a sink groups processor to failover and set priorities for all individual sinks. All specified priorities must be unique. Furthermore, upper limit to fail over time can be set (in milliseconds) using maxpenalty property.

Required properties are in bold.

Property Name Default Description
processor.sinks Space separated list of sinks that are participating in the group
processor.type default The component type name, needs to be failover
processor.priority.<sinkName> <sinkName> must be one of the sink instances associated with the current sink group
processor.maxpenalty 30000 (in millis)

Example for agent named agent_foo:

agent_foo.sinkgroups = group1
agent_foo.sinkgroups.group1.sinks = sink1 sink2
agent_foo.sinkgroups.group1.processor.type = failover
agent_foo.sinkgroups.group1.processor.priority.sink1 = 5
agent_foo.sinkgroups.group1.processor.priority.sink2 = 10
agent_foo.sinkgroups.group1.processor.maxpenalty = 10000

Load balancing Sink Processor

Load balancing sink processor provides the ability to load-balance flow over multiple sinks. It maintains an indexed list of active sinks on which the load must be distributed. Implementation supports distributing load using either via ROUND_ROBIN, RANDOM, ROUND_ROBIN_BACKOFF, or RANDOM_BACKOFF selection mechanisms. The choice of selection mechanism defaults to ROUND_ROBIN type, but can be overridden via configuration. Custom selection mechanisms are supported via custom classes that inherits from LoadBalancingSelector.

When invoked, this selector picks the next sink using its configured selection mechanism and invokes it. For ROUND_ROBIN and RANDOM In case the selected sink fails to deliver the event, the processor picks the next available sink via its configured selection mechanism. This implementation does not blacklist the failing sink and instead continues to optimistically attempt every available sink. If all sinks invocations result in failure, the selector propagates the failure to the sink runner. The BACKOFF variants will blacklist sinks that fail, removing them for selection for a given timeout. When the timeout ends, if the sink is still unresponsive timeout is increased exponentially to avoid potentially getting stuck in long waits on unresponsive sinks.

Required properties are in bold.

Property Name Default Description
processor.sinks   Space separated list of sinks that are participating in the group
processor.type default The component type name, needs to be load_balance
processor.selector ROUND_ROBIN Selection mechanism. Must be either ROUND_ROBIN, RANDOM ROUND_ROBIN_BACKOFF, RANDOM_BACKOFF or custom FQDN to class that inherits from LoadBalancingSelector
processor.selector.maxBackoffMillis 30000 used by backoff selectors to limit exponential backoff in miliseconds

Example for agent named agent_foo:

agent_foo.sinkgroups = group1
agent_foo.sinkgroups.group1.sinks = sink1 sink2
agent_foo.sinkgroups.group1.processor.type = load_balance
agent_foo.sinkgroups.group1.processor.selector = random

Custom Sink Processor

Custom sink processors are not supported at the moment.

Flume Interceptors

Flume has the capability to modify/drop events in-flight. This is done with the help of interceptors. Interceptors are classes that implement org.apache.flume.interceptor.Interceptor interface. An interceptor can modify or even drop events based on any criteria chosen by the developer of the interceptor. Flume supports chaining of interceptors. This is made possible through by specifying the list of interceptor builder class names in the configuration. Interceptors are specified as a whitespace separated list in the source configuration. The order in which the interceptors are specified is the order in which they are invoked. The list of events returned by one interceptor is passed to the next interceptor in the chain. Interceptors can modify or drop events. If an interceptor needs to drop events, it just does not return that event in the list that it returns. If it is to drop all events, then it simply returns an empty list. Interceptors are named components, here is an example of how they are created through configuration:

agent_foo.sources = source_foo
agent_foo.channels = channel-1
agent_foo.sources.source_foo.interceptors = a b
agent_foo.sources.source_foo.interceptors.a.type = org.apache.flume.interceptor.HostInterceptor$Builder
agent_foo.sources.source_foo.interceptors.a.preserveExisting = false
agent_foo.sources.source_foo.interceptors.a.hostHeader = hostname
agent_foo.sources.source_foo.interceptors.b.type = org.apache.flume.interceptor.TimestampInterceptor$Builder

Note that the interceptor builders are passed to the type config parameter. The interceptors are themselves configurable and can be passed configuration values just like they are passed to any other configurable component. In the above example, events are passed to the HostInterceptor first and the events returned by the HostInterceptor are then passed along to the TimestampInterceptor.

Timestamp Interceptor

This interceptor inserts into the event headers, the time in millis at which it processes the event. This interceptor inserts a header with key timestamp whose value is the relevant timestamp. This interceptor can preserve an existing timestamp if it is already present in the configuration.

Property Name Default Description
type The component type name, has to be TIMESTAMP
preserveExisting false If the timestamp already exists, should it be preserved - true or false

Example for agent named agent_foo:

agent_foo.sources = source1
agent_foo.channels = channel1
agent_foo.sources.source1.channels =  channel1
agent_foo.sources.source1.type = SEQ
agent_foo.sources.source1.interceptors = inter1
agent_foo.sources.source1.interceptors.inter1.type = timestamp

Host Interceptor

This interceptor inserts the hostname or IP address of the host that this agent is running on. It inserts a header with key host or a configured key whose value is the hostname or IP address of the host, based on configuration.

Property Name Default Description
type The component type name, has to be HOST
preserveExisting false If the host header already exists, should it be preserved - true or false
useIP true Use the IP Address if true, else use hostname.
hostHeader host The header key to be used.

Example for agent named agent_foo:

agent_foo.sources = source_foo
agent_foo.channels = channel-1
agent_foo.sources.source_foo.interceptors = host_int
agent_foo.sources.source_foo.interceptors.host_int.type = host
agent_foo.sources.source_foo.interceptors.host_int.hostHeader = hostname

Static Interceptor

Static interceptor allows user to append a static header with static value to all events.

The current implementation does not allow specifying multiple headers at one time. Instead user might chain multiple static interceptors each defining one static header.

Property Name Default Description
type The component type name, has to be STATIC
preserveExisting true If configured header already exists, should it be preserved - true or false
key key Name of header that should be created
value value Static value that should be created

Example for agent named agent_foo:

agent_foo.sources = source1
agent_foo.channels = channel1
agent_foo.sources.source1.channels =  channel1
agent_foo.sources.source1.type = SEQ
agent_foo.sources.source1.interceptors = inter1
agent_foo.sources.source1.interceptors.inter1.type = static
agent_foo.sources.source1.interceptors.inter1.key = datacenter
agent_foo.sources.source1.interceptors.inter1.value = NEW_YORK

Regex Filtering Interceptor

This interceptor filters events selectively by interpreting the event body as text and matching the text against a configured regular expression. The supplied regular expression can be used to include events or exclude events.

Property Name Default Description
type The component type name has to be REGEX_FILTER
regex ”.*” Regular expression for matching against events
excludeRegex false If true, regex determines events to exclude, otherwise regex determines events to include.

Flume Properties

Property Name Default Description
flume.called.from.service If this property is specified then the Flume agent will continue polling for the config file even if the config file is not found at the expected location. Otherwise, the Flume agent will terminate if the config doesn’t exist at the expected location. No property value is needed when setting this property (eg, just specifying -Dflume.called.from.service is enough)

Property: flume.called.from.service

Flume periodically polls, every 30 seconds, for changes to the specified config file. A Flume agent loads a new configuration from the config file if either an existing file is polled for the first time, or if an existing file’s modification date has changed since the last time it was polled. Renaming or moving a file does not change its modification time. When a Flume agent polls a non-existent file then one of two things happens: 1. When the agent polls a non-existent config file for the first time, then the agent behaves according to the flume.called.from.service property. If the property is set, then the agent will continue polling (always at the same period – every 30 seconds). If the property is not set, then the agent immediately terminates. ...OR... 2. When the agent polls a non-existent config file and this is not the first time the file is polled, then the agent makes no config changes for this polling period. The agent continues polling rather than terminating.

Log4J Appender

Appends Log4j events to a flume agent’s avro source. A client using this appender must have the flume-ng-sdk in the classpath (eg, flume-ng-sdk-1.2.0.jar). Required properties are in bold.

Property Name Default Description
Hostname The hostname on which a remote Flume agent is running with an avro source.
Port The port at which the remote Flume agent’s avro source is listening.

Sample log4j.properties file:

#...
log4j.appender.flume = org.apache.flume.clients.log4jappender.Log4jAppender
log4j.appender.flume.Hostname = example.com
log4j.appender.flume.Port = 41414

# configure a class's logger to output to the flume appender
log4j.logger.org.example.MyClass = DEBUG,flume
#...

Security

The HDFS sink supports Kerberos authentication if the underlying HDFS is running in secure mode. Please refer to the HDFS Sink section for configuring the HDFS sink Kerberos-related options.

Monitoring

Monitoring in Flume is still a work in progress. Changes can happen very often. Several Flume components report metrics to the JMX platform MBean server. These metrics can be queried using Jconsole.

Ganglia Reporting

Flume can also report these metrics to Ganglia 3 or Ganglia 3.1 metanodes. To report metrics to Ganglia, a flume agent must be started with this support. The Flume agent has to be started by passing in the following parameters as system properties prefixed by flume.monitoring., and can be specified in the flume-env.sh:

Property Name Default Description
type The component type name, has to be GANGLIA
hosts Comma separated list of hostname:port
pollInterval 60 Time, in seconds, between consecutive reporting to ganglia server
isGanglia3 false Ganglia server version is 3. By default, Flume sends in ganglia 3.1 format

We can start Flume with Ganglia support as follows:

$ bin/flume-ng agent --conf-file example.conf --name agent1 -Dflume.monitoring.type=GANGLIA -Dflume.monitoring.hosts=com.example:1234,com.example2:5455

Any custom flume components should use Java MBean ObjectNames which begin with org.apache.flume for Flume to report the metrics to Ganglia. This can be done by adding the ObjectName as follows(the name can be anything provided it starts with org.apache.flume):

ObjectName objName = new ObjectName("org.apache.flume." + myClassName + ":type=" + name);

ManagementFactory.getPlatformMBeanServer().registerMBean(this, objName);

JSON Reporting

Flume can also report metrics in a JSON format. To enable reporting in JSON format, Flume hosts a Web server on a configurable port. Flume reports metrics in the following JSON format:

{
"typeName1.componentName1" : {"metric1" : "metricValue1", "metric2" : "metricValue2"},
"typeName2.componentName2" : {"metric3" : "metricValue3", "metric4" : "metricValue4"}
}

Here is an example:

{
"CHANNEL.fileChannel":{"EventPutSuccessCount":"468085",
                      "Type":"CHANNEL",
                      "StopTime":"0",
                      "EventPutAttemptCount":"468086",
                      "ChannelSize":"233428",
                      "StartTime":"1344882233070",
                      "EventTakeSuccessCount":"458200",
                      "ChannelCapacity":"600000",
                      "EventTakeAttemptCount":"458288"},
"CHANNEL.memChannel":{"EventPutSuccessCount":"22948908",
                   "Type":"CHANNEL",
                   "StopTime":"0",
                   "EventPutAttemptCount":"22948908",
                   "ChannelSize":"5",
                   "StartTime":"1344882209413",
                   "EventTakeSuccessCount":"22948900",
                   "ChannelCapacity":"100",
                   "EventTakeAttemptCount":"22948908"}
}
Property Name Default Description
type The component type name, has to be HTTP
port 41414 The port to start the server on.

We can start Flume with Ganglia support as follows:

$ bin/flume-ng agent --conf-file example.conf --name agent1 -Dflume.monitoring.type=HTTP -Dflume.monitoring.port=34545

Metrics will then be available at http://<hostname>:<port>/metrics webpage. Custom components can report metrics as mentioned in the Ganglia section above.

Custom Reporting

It is possible to report metrics to other systems by writing servers that do the reporting. Any reporting class has to implement the interface, org.apache.flume.instrumentation.MonitorService. Such a class can be used the same way the GangliaServer is used for reporting. They can poll the platform mbean server to poll the mbeans for metrics. For example, if an HTTP monitoring service called HTTPReporting can be used as follows:

$ bin/flume-ng agent --conf-file example.conf --name agent1 -Dflume.monitoring.type=com.example.reporting.HTTPReporting -Dflume.monitoring.node=com.example:332
Property Name Default Description
type The component type name, has to be FQCN

Troubleshooting

Handling agent failures

If the Flume agent goes down then the all the flows hosted on that agent are aborted. Once the agent is restarted, then flow will resume. The flow using jdbc or other stable channel will resume processing events where it left off. If the agent can’t be restarted on the same, then there an option to migrate the database to another hardware and setup a new Flume agent that can resume processing the events saved in the db. The database HA futures can be leveraged to move the Flume agent to another host.

Compatibility

HDFS

Currently Flume supports HDFS 0.20.2 and 0.23.

AVRO

TBD

Additional version requirements

TBD

Tracing

TBD

More Sample Configs

TBD

Component Summary

Component Interface Type Implementation Class
org.apache.flume.Channel MEMORY org.apache.flume.channel.MemoryChannel
org.apache.flume.Channel JDBC org.apache.flume.channel.jdbc.JdbcChannel
org.apache.flume.Channel org.apache.flume.channel.recoverable.memory.RecoverableMemoryChannel
org.apache.flume.Channel FILE org.apache.flume.channel.file.FileChannel
org.apache.flume.Channel org.apache.flume.channel.PseudoTxnMemoryChannel
org.apache.flume.Channel org.example.MyChannel
org.apache.flume.Source AVRO org.apache.flume.source.AvroSource
org.apache.flume.Source NETCAT org.apache.flume.source.NetcatSource
org.apache.flume.Source SEQ org.apache.flume.source.SequenceGeneratorSource
org.apache.flume.Source EXEC org.apache.flume.source.ExecSource
org.apache.flume.Source SYSLOGTCP org.apache.flume.source.SyslogTcpSource
org.apache.flume.Source SYSLOGUDP org.apache.flume.source.SyslogUDPSource
org.apache.flume.Source org.apache.flume.source.avroLegacy.AvroLegacySource
org.apache.flume.Source org.apache.flume.source.thriftLegacy.ThriftLegacySource
org.apache.flume.Source org.example.MySource
org.apache.flume.Sink NULL org.apache.flume.sink.NullSink
org.apache.flume.Sink LOGGER org.apache.flume.sink.LoggerSink
org.apache.flume.Sink AVRO org.apache.flume.sink.AvroSink
org.apache.flume.Sink HDFS org.apache.flume.sink.hdfs.HDFSEventSink
org.apache.flume.Sink org.apache.flume.sink.hbase.HBaseSink
org.apache.flume.Sink org.apache.flume.sink.hbase.AsyncHBaseSink
org.apache.flume.Sink FILE_ROLL org.apache.flume.sink.RollingFileSink
org.apache.flume.Sink IRC org.apache.flume.sink.irc.IRCSink
org.apache.flume.Sink org.example.MySink
org.apache.flume.ChannelSelector REPLICATING org.apache.flume.channel.ReplicatingChannelSelector
org.apache.flume.ChannelSelector MULTIPLEXING org.apache.flume.channel.MultiplexingChannelSelector
org.apache.flume.ChannelSelector org.example.MyChannelSelector
org.apache.flume.SinkProcessor DEFAULT org.apache.flume.sink.DefaultSinkProcessor
org.apache.flume.SinkProcessor FAILOVER org.apache.flume.sink.FailoverSinkProcessor
org.apache.flume.SinkProcessor LOAD_BALANCE org.apache.flume.sink.LoadBalancingSinkProcessor
org.apache.flume.interceptor.Interceptor TIMESTAMP org.apache.flume.interceptor.TimestampInterceptor$Builder
org.apache.flume.interceptor.Interceptor HOST org.apache.flume.interceptor.HostInterceptor$Builder
org.apache.flume.interceptor.Interceptor STATIC org.apache.flume.interceptor.StaticInterceptor$Builder

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