Table Of Contents
Collection Manager Software Package
Priority Queues and Persistent Buffers
TA Adapter Memory Requirements
RAG Adapter Aggregation Buckets
Collection Manager Overview
Revised: June 02, 2011, OL-7208-13Introduction
This chapter provides detailed information about the functionality of collection manager components.
This module describes how the Cisco Service Control Management Suite (SCMS) Collection Manager (CM) works. It describes the Raw Data Records (RDRs) that the Service Control Engine (SCE) platforms produce and send to the Collection Manager, and provides an overview of the components of the CM software package. It also gives an overview of the database used to store the RDRs.
•
Collection Manager Software Package
Data Collection Process
Cisco SCE platforms create RDRs whose specifications are defined by the application running on the SCE platform, such as the Cisco Service Control Application for Broadband (SCA BB).
1.
2.
3.
You can use preinstalled utility scripts to customize many of the parameters that influence the behavior of the CM.
Raw Data Records
Raw Data Records (RDRs) are reports produced by SCE platforms. The list of RDRs, their fields, and their semantics depend on the specific service control protocol (SCP) application. Each RDR type has a unique ID known as an RDR tag.
Table 2-1 contains examples of RDRs produced by SCP applications:
Collection Manager Software Package
The Collection Manager software package is a group of processing and sorting modules. These include the following components:
•
Raw Data Record Server
As each incoming raw data record (RDR) arrives from an SCE platform, the RDR server adds an arrival timestamp and the ID of the source SCE platform to it, and then sends the RDR to the categorizer.
Categorizer
A categorizer classifies each RDR according to its RDR tag. It decides the destination adapters for the RDR and through which priority queue it should be sent.
An RDR can be mapped to more than one adapter. A qualified technician defines the flow in a configuration file based on user requirements.
Priority Queues and Persistent Buffers
Each adapter has one or more Priority Queues; a persistent buffer is assigned to each priority queue.
A priority queue queues each RDR according to its priority level and stores it in a persistent buffer until the adapter processes it.
A persistent buffer is a nonvolatile storage area that ensures that the system processes RDRs even in cases of hardware, software, or power failures.
Adapter Description
Adapters are software modules that transform RDRs to match the target system's requirements, and distribute the RDRs upon request. At this time, the following adapters are shipped with the system:
•
•
Some of the adapters send data to the database or write it to CSV files. The structures of the database tables, and the location and structures of these CSV files are described in the Cisco Service Control Application for Broadband Reference Guide.
Each adapter has its own configuration file; all the configuration files are similar in structure. For a sample RAG adapter configuration file, see ragadapter.conf File, page A-5.
JDBC Adapter
The JDBC adapter receives RDRs, processes them, and stores the records in a database.
This adapter is designed to be compatible with any database server that is JDBC-compliant, and transforms the records accordingly. The JDBC adapter can be configured to use a database operating on a remote machine.
The JDBC adapter is preconfigured to support the following databases:
•
•
Note
recyclebin=off•
Comma Separated Value Adapter
The comma separated value (CSV) adapter receives RDRs, processes them, and writes the records to files on the disk in comma-separated value format. Using standard mechanisms such as FTP, a service provider's OSS or a third-party billing system can retrieve these records to generate enhanced accounting and network traffic analysis records.
Topper/Aggregator Adapter
The topper/aggregator (TA) adapter receives subscriber usage RDRs, aggregates the data they contain, and outputs 'Top Reports' to the database and aggregated daily statistics of all subscribers (not just the top consumers) to CSV files. Top Reports are lists of the top subscribers for different metrics (for example, the top 50 volume or session consumers in the last hour).
This adapter maintains a persistent saved state (saved to disk) to minimize any data loss in case of failure.
The TA adapter, which uses the JDBC adapter infrastructure, can be configured to use any JDBC-compliant database, either locally or remotely.
Note
•
TA Adapter Cycles
The TA Adapter works in two cycles: short and long. Cycles are fixed intervals at the end of which the adapter can output its aggregated information to the database and to a CSV file. The default interval for the short cycle is 1 hour; for the long cycle it is 24 hours (every day at midnight). The intervals (defined in minutes) and their start and end times are configurable.
Note
The activities in each cycle differ slightly, as follows:
•
–
–
•
–
–
–
TA Adapter Memory Requirements
To work correctly, you must dedicate a sufficient amount of memory to the TA adapter. Configure the value in the cm.conf configuration file in the following location:
[adapter_mem] com.cisco.scmscm.adapters.topper.TAAdapter=<Memory for TA Adapter>To calculate the recommended amount of memory to dedicate to the TA adapter, use the following formula:
Memory (Bytes) = 2.5 * NUM_SUBSCRIBERS * (AVG_SUBS_ID_LENGTH + 64*NUM_SERVICES + 12*NUM_TOP_ENTRIES)
Where:
•
This is usually a high number; especially when working in anonymous subscriber mode.
To display an estimate of the number of subscribers that are known to the CM, use the following command:
~/setup/mbean.py --getattr=Subscribers DCAdapters com.cisco.scmscm.adapters.topper.TAAdapter•
In most cases, this is approximately 20.
•
•
Note
For Solaris JRE 32-bit, the configured memory should not be over 3.5 GB.
For Solaris JRE 64-bit, you can set higher values for the configured memory. To configure the TA or RAG Adapters to run with the JRE 64-bit see [adapter_mem] Section, page B-3.
Real-Time Aggregating Adapter
The real-time aggregating (RAG) adapter processes RDRs of one or more types and aggregates the data from predesignated field positions into buckets. The contents of the buckets are written to CSV files.
•
RAG Adapter Aggregation Buckets
A RAG adapter aggregation bucket is indexed by combining values from fields in the RDR. The indexing relation can be one-to-one or many-to-one.
The values in the bucket-identifying fields are processed using closures (equivalence classes), which are configured per type of RDR.
Example:
Bucket-identifying field = field number 3 Closures: 4 = 4,5,6; 10 = 8,10,11 Value in field 3 = 4, 5, or 6; field reported as 4 Value in field 3 = 8, 10, or 11; field reported as 10The adapter can be configured to monitor the values in certain fields for change relative to the values in the first RDR that entered the bucket. For each monitored field, an action is performed when a value change is detected. The supported actions are:
•
•
Buckets, closures, triggers, and trigger actions are defined in an XML file. For a sample XML file, see ragadapter.xml File, page A-6.
Flushing a Bucket
When a bucket is flushed, it is written as one line to a CSV file.
The trigger for flushing a bucket (a checkpoint) is the earliest occurrence of any of the following:
•
•
•
•
The trigger to close a CSV file is the earliest occurrence of one of the following:
•
•
•
Using Databases
The CM can use either a bundled database or an external database to store RDRs supplied by the system's SCE platforms.
Using the Bundled Database
In bundled mode, the CM uses the Sybase Adaptive Server Enterprise database, which supports transaction-intensive enterprise applications, allows you to store and retrieve information online, and can warehouse information as needed.
The Sybase database is located on the same server as the other CM components. It uses a simple schema consisting of a group of small, simple tables.
1.
2.
Database maintenance is performed using operating system commands and scripts. The CM supports automatic purging of old records from the bundled database. By default, the report tables are automatically purged of every record that is more than two weeks old. The records are polled once every hour. Database maintenance can be configured using the dbperiodic.py utility script. For more information, see Managing the Periodic Deletion of Old Records, page 5-4.
Using an External Database
Any JDBC-compliant database (for example, Oracle or MySQL) may be used with the CM in conjunction with the JDBC adapter. In this case, the database can be local or remote. You should:
•
•
•
For details about configuring the CM to work with an external database, see Managing Databases and the Comma Separated Value Repository, page 5-1.
