Requirements, Parallel processing for load operations – HP Neoview Release 2.4 Software User Manual
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Requirements
These are the requirements to use the Trickle Feed feature:
•
ActiveMQ (JMS provider), which is included with the Java client package
•
A separate (and dedicated) instance of the Transporter Java client
A JMS trickle feed load is similar to loads from flat files or named pipes, except for the following
differences:
•
Workflow
When the Java client parses the control file and determines that the source is JMS, a trickle
feed process known as a JMS Consumer is launched to consume data from the JMS queue.
The JMS Consumer waits up to
for data to arrive. If no data arrives
during this time, the JMS Consumer shuts down.
•
JMS Queue Message Handling
— Each message received is considered a single data record.
— Messages are in JMS text format, and may be either delimited or fixed-width format.
— Messages are read from the JMS Queue asynchronously and removed automatically as
they are read.
— Transporter continues to load data in real time continuously, a record at a time, until
the JMS Consumer reads the
sequence.
•
Message Characteristics
— Message domain is Point-To-Point – each message has a single consumer, and the
message is retained in the queue until it is consumed.
— Message format is JMS text message type.
•
Control File Specification
sourcename jms jmsname [options provider-options]
jmsname
The name of the queue.
provider-options
The options are:
—
—
—
—
•
Limitations
The Java Consumer process commits to the JMS Queue after the data (row) is committed
on the Neoview platform. However, there is a window where a row may be inserted twice.
This situation could occur if the row is committed on the Neoview platform, but the network
connection between the client and server is dropped before confirmation is received by the
client.
For information about Java, refer to these web sites:
•
•
Parallel Processing for Load Operations
If you want job entries in a load operation to process in parallel, you must set
= true
. These considerations apply:
Parallel Processing for Load Operations
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