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 LiveView Peer-Based Recovery Sample for TCM eFTL Message Bus
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Overview:

This sample demonstrates the LiveView delayed peer-based recovery capability 
when using the eFTL message bus service. TIBCO Cloud Messaging (TCM) can 
optionally use eFTL. See the TIBCO Streaming eFTL adapter documentation to 
ensure the eFTL dependencies are properly configured.  

Message buses such as Kafka support replaying older messages based on an 
offset, or sequence number. LiveView recovery with such buses is fairly simple 
and does not need the delayed recovery capability. See the Kafka recovery 
sample for more information.

Buses such as eFTL and FTL, even when configured with persistence,
do not support playing older messages that were not previously 
received and unacknowledged. eFTL and FTL do provide monotonically increasing
storage message ids which can use used to uniquely identify messages. 
For buses of this kind, LiveView can use delayed peer-based recovery
with perfect fidelity as demonstrated in this sample.

To avoid missing data from eFTL while recovery is in progress, the sample must 
first subscribe to the eFTL channel. Only after the subscription is 
successful will the sample start recovering data from peer nodes, and storing 
incoming eFTL data, if any, while peer recovery is ongoing.

During startup, a LiveView node looks for peer nodes in the same cluster and 
starts the delayed recovery process if there is at least one peer node 
available. After peer recovery is complete, retained data from the eFTL 
subscription that have higher eFTL storage message ids are sent to the
LiveView table and publishing transitions to the real-time data coming from the bus.
It's the eFTL monotonically increasing storage message id that allows
LiveView to not skip any data and also not publish the same data twice. 

Sample Requirements:

To run this sample, an available eFTL service is required. The sample uses
eFTL 6.5, and assumes the eFTL server is running at 
ws://localhost:8585 by default.

To set up a local eFTL/FTL service, make sure you have FTL 6.5 and eFTL 6.5 
installed. The FTL installation directory (such as /opt/tibco/ftl/6.5/samples) 
contains a samples directory with a readme.txt that documents how to 
start an eFTL server on the default port. Starting an eFTL server is required 
to run this sample.

For more information about eFTL configurations, see 
    https://docs.tibco.com/products/tibco-eftl-enterprise-edition-6-5-0

Running the Sample:

After starting the eFTL/FTL service, the next step is to publish messages to 
the service:

    Right-click on lv_sample_eft_message_publisher and run it as
    an EventFlow Fragment.

Only one publisher instance is needed.

Once the eFTL service and publisher are running:

    1) Go to Run > Run Configurations and create a new LiveView fragment 
       run configuration. 
    2) Click Browse and select this sample project as the LiveView Project.
    3) Set the LiveView engine port to 10080.
    4) Make sure only engine.conf is selected as the configuration file 
       (by default every file is selected). 
    5) Go to the Node tab and enter peer1$(SeqNum:_) as the node name. 
    6) Click Run.

The above steps start the first node in the cluster. Repeat the steps 
for the peer node, but set the LiveView engine port to 10081 and use
peer2$(SeqNum:_) for the node name.

Expect to see data available on both localhost:10080 and localhost:10081.

Sample Script Details:

The script lv-test-consistency.sh compares data between two Data layer (DL) servers running
in the cluster. To validate that both DLs have indentical data.

The script lv-test-no-duplicates.sh checks whether there is any row that is 
published more than once on the DLs. The ItemsSales table contains the field
updateCount that increments by 1 every time the row is published. The script
validates that no row has an updateCount greater than 1.

Running the servers as installed applications:

There are deploy projects included in the sample to make it
easier to create deployable applications. For details on building, installing
and starting applications, see the StreamBase documentation.