I have always found the Integrated Heartbeat for GoldenGate very useful for quickly identifying replication trends and potential slowness in the replication path. Luckily in GoldenGate Big Data Adapter Version 19c they have extended this functionality for the Big Data Adapter. My goal with this blog post is to show how easy it is to enable the heartbeat and to demonstrate a python script to utilize the data the heartbeat produces.

First, enable the heartbeat on the source just as you normally would. I won’t cover how to do that in this post, but for GoldenGate 19c, the instructions can be found here:

https://docs.oracle.com/en/middleware/goldengate/core/19.1/gclir/add-heartbeattable.html#GUID-126E30A2-DC7A-4C93-93EC-0EB8BA7C13CB

Enabling the HeartBeat for the Big Data Adapter

Luckily, enabling the heartbeat for the big data adapter is just as easy as in the normal Goldengate CLI. The official reference is here:

https://docs.oracle.com/en/middleware/goldengate/big-data/19.1/gbdin/automatic-heartbeat-bigdata.html#GUID-56DF810A-A417-45DB-A3ED-2D902B800778

For expedience, I will show the basic usage of the command here. After logging into GGSCI, enabling the target heartbeat is as easy as:

Oracle GoldenGate for Big Data
Version 19.1.0.0.8 (Build 002)

Oracle GoldenGate Command Interpreter
Version 19.1.0.0.210228 OGGCORE_19.1.0.0.0OGGBP_PLATFORMS_210212.1752.2
Linux, x64, 64bit (optimized), Generic  on Mar 18 2021 07:13:36
Operating system character set identified as UTF-8.

Copyright (C) 1995, 2021, Oracle and/or its affiliates. All rights reserved.



GGSCI (orcl-vbox2.localdomain.com) 1> ADD HEARTBEATTABLE
Heartbeat table is now enabled.
HEARTBEAT configuration file dirprm/heartbeat.properties
heartbeat.enabled=true
heartbeat.frequency=60
heartbeat.retention_time=30
heartbeat.purge.frequency=1
heartbeat.db.name=BigData

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Now that the heartbeat has been enabled where does the data go? The heartbeat information (by default) is under your GOLDENGATE_HOME/dirtmp directory in the form of JSON files:

RKFJSCON-hb.json – Data for Last Heartbeat

The last heartbeat recorded looks like this:

{
“localDatabase” : “BigData”,
“heartbeatTimestamp” : “2021-08-27 13:17:14.149808000”,
“remoteDatabase” : “VBOXNCDB”,
“incomingExtract” : “E_HR_CL”,
“incomingRoutingPath” : “P_HR_CL”,
“incomingReplicat” : “RKFJSCON”,
“incomingHeartbeatTs” : “2021-08-27 13:17:14.149808000”,
“incomingExtractTs” : “2021-08-27 13:17:16.822345000”,
“incomingRoutingTs” : “2021-08-27 13:17:17.275030000”,
“incomingReplicatTs” : “2021-08-27 13:17:20.411229000”,
“outgoingReplicat” : “RKFJSCON”,
“outgoingReplicatTs” : “2021-08-27 13:17:20.412000000”
}

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The every time a new heartbeat arrives the last heartbeat is written to a historical file by day up to the retention period where the data is then deleted:

{
“records” : [ {
“localDatabase” : “BigData”,
“heartbeatTimestamp” : “2021-08-27 00:00:14.110627000”,
“remoteDatabase” : “VBOXNCDB”,
“incomingExtract” : “E_HR_CL”,
“incomingRoutingPath” : “P_HR_CL”,
“incomingReplicat” : “RKFJSCON”,
“incomingHeartbeatTs” : “2021-08-27 00:00:14.110627000”,
“incomingExtractTs” : “2021-08-27 00:00:16.213547000”,
“incomingRoutingTs” : “2021-08-27 00:00:17.371348000”,
“incomingReplicatTs” : “2021-08-27 00:00:20.147079000”,
“outgoingReplicat” : “RKFJSCON”,
“outgoingReplicatTs” : “2021-08-27 00:00:20.170000000”
}, {
More json records
}, {
“localDatabase” : “BigData”,
“heartbeatTimestamp” : “2021-08-27 13:21:14.178962000”,
“remoteDatabase” : “VBOXNCDB”,
“incomingExtract” : “E_HR_CL”,
“incomingRoutingPath” : “P_HR_CL”,
“incomingReplicat” : “RKFJSCON”,
“incomingHeartbeatTs” : “2021-08-27 13:21:14.178962000”,
“incomingExtractTs” : “2021-08-27 13:21:16.602223000”,
“incomingRoutingTs” : “2021-08-27 13:21:17.675216000”,
“incomingReplicatTs” : “2021-08-27 13:21:21.481484000”,
“outgoingReplicat” : “RKFJSCON”,
“outgoingReplicatTs” : “2021-08-27 13:21:21.481000000”
} ]
}

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So as you can see the heartbeat data is now in json format to be able to write alerts, OEM extensions or whatever else you see fit. Check out my next blog post on how to report on this data using a simple Python script!