Chapter 27: Working with Binary Large Objects (Blobs)

Chapter 27: Working with Binary Large Objects (Blobs) 

Binary Large Objects 

Binary Large Objects (blobs) are binary data of variable length. CA Workload Automation 

AE supports blobs in job definitions, and after they are defined, they are stored in the 

database. This allows the blob data to be shared by jobs running on multiple computers. 

To understand the advantages of using blobs in CA Workload Automation AE 

environment, refer to the following example, which explains the process that is used to 

share data amongst the jobs that are running on a single computer: 

1. When the jobs are running on a single computer, you can define a command job to 

run a program that outputs the data to a file using the std_out_file attribute. 

2. When the job is completed, a file is created in the location specified by the 

std_out_file attribute. 

3. All the other jobs that depend on this output data can access this file. 

4. You can also define a second command job to run a program that reads the output 

data of the previous job, by specifying the file name in the std_in_file attribute. 

5. This second command job opens the file specified by the std_in_file attribute and 

passes the data to the program, allowing it to complete successfully. 

Based on this example, as the output data is stored in a file on one computer, it is not 

available to all the other jobs that are scheduled to run on other computers. However, 

the use of blobs allows the data that is saved as output by a job on one computer to be 

shared by all the other jobs that are running across multiple computers. 

Also, you can define a command job to run a program that uploads the output data to 

the database as a blob using the std_out_file attribute. You can also define a second 

command job to run a program that reads the blob data of the previous job using the 

std_in_file attribute. The second command job downloads the blob data specified by 

the std_in_file attribute from the database and passes the data to the program, allowing 

it to complete successfully. 

 Types of Blobs 

Blob data can be of the following types: 

Binary Data 

Requires a program that understands the format of the data to interpret the bytes 

in binary data. For example: 

Multimedia files which include the following: 

■ Images 

■ Video files 

■ Audio files

Textual Data 

Requires an operating system that can interpret the bytes in textual data, which 

contains the characters that conform to the ASCII standard. 

Note: Some operating systems handle the specification of a new line in the textual 

data differently. In this instance, you must convert the necessary textual data when 

it is copied across operating systems. 

CA Workload Automation AE allows you to specify the type of blob data that is 

being used and converts the textual data when it is downloaded across multiple 

operating systems. 

Types of Blobs 

CA Workload Automation AE supports the following types of blobs: 

■ Job blobs 

■ Global blobs 

Note: If you install the 64-bit agent using the CA Workload Automation Agent for UNIX, 

Linux, or Windows DVD, you cannot run jobs that contain globs or blobs as input or 

output. The native CA Workload Automation AE client or SDK runs only in 32-bit mode 

and does not support being called by a 64-bit application. 

Job Blobs 

Job blobs are associated with an existing CA Workload Automation AE job and are 

referenced by the job name. Job blobs can either be created at the time of the job 

definition or after the job has been defined. They are deleted when the job is deleted. 

There are three types of job blobs, which include the following: 

Input 

Contains the input data that is reserved for the job to which they are associated in 

textual data format. 

Output 

Stores the program output messages of a running job in textual or binary data 

format. 

Error 

Stores the error messages of a running job in textual or binary data format. 

Input Job Blobs 

Input blobs are uploaded to the database using JIL. You can insert an input job blob 

multiple times. Each time it is inserted, it acquires a new version number. 

When the job starts, the most recent version of the job input blob is used. All the earlier 

versions of the blob remain in the database until they are manually deleted. If you 

delete an input job blob, only the active version of the input job blob is deleted. The 

version which was prior to the deleted version becomes the new active version. 

When you run a job, the CA Workload Automation AE agent downloads the active 

version of job's input blob from the database into a temporary file on the computer. 

This file is then passed into the standard input of the program that is executed by the 

job. When the job completes, the temporary file containing the input blob data is 

deleted. The blob in the database, however, is not deleted and remains as the active 

version for subsequent job runs. 

 Global Blobs 

Output and Error Job Blobs 

Output and error job blobs store the program output and error messages of a running 

job. When you run a job, the CA Workload Automation AE agent creates temporary files 

on the computer that are used to capture the standard output and standard error 

messages from the program that was executed by the job. After the job has completed 

its run, the agent uploads the files containing the output data as blobs into the 

database, overwriting the existing files, and deletes the temporary files. An output job 

blob can be used as input by another job. An error job blob, on the other hand, cannot 

be used as input by another job. 

Global Blobs 

Global blobs are general purpose blobs in textual or binary data format. Like the CA 

Workload Automation AE global variables, they are referenced by a unique name. You 

can either upload the global blobs to the database using JIL or they can be uploaded by 

the CA Workload Automation AE agent, after a job has completed its run. After a global 

blob is created, it is available to any job as input. Global blobs remain in the database 

until they are deleted using JIL. 

Manage Blobs Using JIL 

The following section describes how to use JIL to do the following: 

■ Upload blobs to the database 

■ Delete blobs from the database 

Note: For more information, see the Reference Guide. 

Blob Attributes 

The following table lists the subcommands and attributes associated with the definition 

or destruction of a blob: 

Task Subcommands Attributes 

Create input job blob insert_job, update_job blob_input or blob_file 

Create input job blob insert_blob blob_input or blob_file 

Delete job blob delete_blob blob_type Blob Attributes 

Task Subcommands Attributes 

Create global blob 

insert_glob blob_mode, blob_input, or 

blob_file 

Delete global blob delete_glob 

The blob_input attribute lets you manually input the contents of a blob containing 

textual data. The blob_input attribute has the following format: 

blob_input: <auto_blobt>textual data</auto_blobt> 

Note: The textual data begins immediately after the auto_blobt XML-style open tag and 

may span multiple lines. JIL recognizes the end of the textual data when it reads the 

auto_blobt XML-style end tag. This implies that the literal character string 

</auto_blobt> cannot form part of the blob_input value. If you want to include this 

character string as part of the textual blob data, use the blob_file attribute. 

The blob_file attribute allows the user to specify the location and name of a file on the 

computer that serves as the input job blob or global blob file. The blob_file attribute has 

the following format: 

blob_file: filename 

Note: If the blob_file attribute is used to specify an input job blob through the 

insert_job or insert_blob subcommand, the file is interpreted as a text-based file. 

Create Input Job Blobs 

To create an input job blob in the database using JIL, do the following: 

■ Upload an input job blob at the time of the definition of the associated job. 

■ Upload an input job blob after you have defined the job. 

Note: Input job blobs are referenced by the name of the job. 

To create an input job blob at the time of the definition of the associated job, use the 

insert_job JIL subcommand and specify either the blob_input or blob_file attributes, as 

follows: 

insert_job: test_job_with_blob 

job_type: cmd 

command: sleep 60 

machine: juno 

owner: jerry@juno 

std_in_file: $$blobt 

blob_input: <auto_blobt>multi-lined text data for job blob 

</auto_blobt> 

or 

blob_file: /test_job_with_blob_file.txt 

To create an input job blob after you have defined the job, use the insert_blob JIL 

subcommand and specify either the blob_input or blob_file attributes, as follows: 

insert_blob: test_job_with_blob 

blob_input: <auto_blobt>multi-lined text data for job blob 

</auto_blobt> 

or 

blob_file: /test_job_with_blob_file.txt 

JIL interprets the file name that is specified in the blob_file attribute as a file that 

contains the textual data and performs a conversion of the new line character. JIL also 

displays the version number of the most recent input job blob. 

Delete Job Blobs 

You can use the JIL delete_blob subcommand to delete the following: 

■ Active version of the input job blob 

■ Output and error job blobs 

You must specify whether to delete the job input or output blob data using the 

blob_type attribute. 

Note: Job blobs are referenced by the name of the job. JIL displays the version number 

of the most recent job input blob. 

To delete the most recent version of the input job blob, use the delete_blob JIL 

subcommand and specify the blob_type attribute with the value of input, as follows: 

delete_blob: test_job_with_blob 

blob_type: input 

To delete the output and error job blobs, use the delete_blob JIL subcommand and 

specify the blob_type attribute with the value of output, as follows: 

delete_blob: test_job_with_blob 

blob_type: output 

Create Global Blobs 

You can use the JIL insert_glob subcommand to upload blobs containing textual or 

binary data. 

As the global blobs are not associated with a job, you must do the following: 

■ Provide a unique identifier. 

■ Specify the mode of the blob data that is being used in the blob_mode attribute. 

Note: If you use the insert_glob JIL subcommand using the same name as an existing 

global blob, the blob data is reinserted into the database. In this case, the original blob 

data is deleted and the new blob data takes its place. 

 Delete Global Blobs 

To create a global blob containing textual data, use the insert_glob JIL subcommand and 

specify the blob_mode attribute with a value of text and either the blob_input or 

blob_file attributes, as follows: 

insert_glob: my_text_global_blob 

blob_mode: text 

blob_input: <auto_blobt>multi-lined text data for job blob 

</auto_blobt> 

or 

blob_file: /my_text_global_blob_file.txt 

Note: JIL interprets the file name that is specified in the blob_file attribute as a file that 

contains textual data and performs a conversion of the new line character. 

To create a global blob containing binary data, use the insert_glob subcommand and 

specify the blob_mode attribute with a value of binary and the blob_file attribute, as 

follows: 

insert_glob: my_binary_global_blob 

blob_mode: binary 

blob_file: /my_binary_global_blob_file 

Note: You cannot use the blob_input attribute to create a global blob that contains the 

binary data. 

Delete Global Blobs 

You can use the JIL delete_glob subcommand to delete the existing global blobs. 

Note: You must provide a unique identifier because global blobs are not associated with 

a job. 

To delete a global blob, use the delete_glob JIL subcommand and provide the name of 

an existing global blob, as follows: 

delete_glob: my_global_blob 

Use Blobs in Job Definitions 

You can use the std_in_file, std_out_file, and std_err_file attributes of the JIL insert_job, 

update_job, or override_job subcommands to reference blobs in addition to files. Based 

on the keyword values you specify for these attributes, CA Workload Automation AE 

downloads a blob for input or uploads a job’s output as blob to meet the job’s needs. 

The keywords are explained in the subsequent sections. 

 Use Blobs in Job Definitions 

std_in_file Attribute 

The keywords that are supported by the std_in_file attribute include the following: 

$$blobt 

Uses the input job blob of the current job as input and treats the blob data as 

textual data. 

$$blob.<job name> 

Uses the output job blob of the specified job as input and treats the blob data as 

binary data. 

$$blobt.<job name> 

Uses the output job blob of the specified job as input and treats the blob data as 

textual data. 

$$glob.<global blob name> 

Uses the specified global blob as input and treats the blob data as binary data. 

$$globt.<global blob name> 

Uses the specified global blob as input and treats the blob data as textual data. 

Note: You cannot use the keyword $$blob to specify the use of the current job's input 

blob. 

To define a job that uses the output blob of its previous run as input 

1. Define the job so that the job's name is in the std_in_file attribute using either the 

$$blob.<job name> or $$blobt.<job name> keyword. 

2. Apply a one-time override of the std_in_file attribute, so that the job reads from a 

local file on the computer on its first run. 

 Use Blobs in Job Definitions 

std_out_file and std_err_file Attributes 

The keywords that are supported by the std_out_file and std_err_file attributes include 

the following: 

$$blob 

Uploads the output or error of the current job as a job blob and treats the data as 

binary data. 

$$blobt 

Uploads the output or error of the current job as a job blob and treats the data as 

textual data. 

$$glob.<global blob name> 

Uploads the output or error of the current job as a global blob with the specified 

name and treats the data as binary data. 

$$globt.<global blob name> 

Uploads the output or error of the current job as a global blob with the specified 

name and treats the data as textual data. 

Note: 

■ You cannot append data to an existing job or global blob. 

■ CA Workload Automation AE does not support the use of > or >> character strings 

in the std_out_file or std_err_file attributes. 

■ Existing blob data is overwritten with the new data after the job run is completed. 

Generate Blob Reports Using Autorep 

You can use the autorep utility to report on and download the input job blobs and global 

blobs. To export the job definition using the autorep –J <jobname> -q option includes 

exporting all versions of that job’s input blob. If a download path is not specified, the 

contents of all input job blobs are displayed along with the job definition. Otherwise, 

autorep downloads the input blob to the specified directory and displays the input blob 

file names numbered by version along with the job definition. Reports generated against 

one or more global blobs are extracted in binary format unless otherwise specified using 

the –a command line parameter. If a download path is not specified, autorep downloads 

the global blob into a temporary directory. 

Options specific to blob and glob data include the following: 

-z globname 

Specifies a glob name or mask whose contents are to be extracted. ALL may be 

specified to extract all globs. Wildcard characters % and _ are also supported. 

-a 

Specifies that the global blob can be downloaded as textual data. 

-f outdir 

Specifies the directory name where input job blobs or global blobs are extracted to. 

The default value is as follows: 

■ UNIX—The /tmp directory. 

■ Windows—The directory represented by the environment variable %TEMP%. 

Note: For more information about autorep reports, job input, and global blobs, see the 

Reference Guide. 

 Generate Blob Reports Using Autorep 

Example: Export Job Definition with Input Blobs 

This example uses the autorep command to export a job definition: 

autorep -J ALL -q 

The output might resemble the following: 

insert_job: test_job 

job_type: cmd 

command: cat 

machine: juno 

owner: jerry@ca 

permission: gx,ge,wx 

alarm_if_fail: 1 

If the job has one or more input blobs tied to it, in addition to the job definition, the 

autorep command extracts each of the job blob definitions, and the output might 

resemble the following: 

insert_job: test_job_with_blob job_type: cmd 

command: cat 

machine: juno 

owner: jerry@juno 

permission: 

std_in_file: $$blobt 

alarm_if_fail: 1 

/* -- test_job_with_blob:insert_blob #1 -- */ 

insert_blob: test_job_with_blob 

blob_input: <auto_blobt>multi-lined text data for job blob 1 

</auto_blobt> 

/* -- test_job_with_blob:insert_blob #2 -- */ 

insert_blob: test_job_with_blob 

blob_input: <auto_blobt> multi-lined text data for job blob 2 

</auto_blobt> 

/* -- test_job_with_blob:insert_blob #3 -- */ 

insert_blob: test_job_with_blob 

blob_input: <auto_blobt> multi-lined text data for job blob 3 

</auto_blobt> 

You can also specify a location to download the blobs using the -f parameter as follows: 

autorep -J ALL -q -f /myblobsdir 

The output might resemble the following: 

insert_job: test_job_with_blob job_type: cmd 

command: cat 

machine: juno 

owner: jerry@juno 

permission: Generate Blob Reports Using Autorep 

std_in_file: $$blobt 

alarm_if_fail: 1 

/* -- test_job_with_blob:insert_blob #1 -- */ 

insert_blob: test_job_with_blob 

blob_file: /myblobsdir/test_job_with_blob_1.txt 

/* -- test_job_with_blob:insert_blob #2 -- */ 

insert_blob: test_job_with_blob 

blob_file: /myblobsdir/test_job_with_blob_2.txt 

/* -- test_job_with_blob:insert_blob #3 -- */ 

insert_blob: test_job_with_blob 

blob_file: /myblobsdir/test_job_with_blob_3.txt 

Example: Generate a Report for All Global Blobs 

This example generates a report that downloads the contents of all global blobs to the 

location /myblobsdir as binary data: 

autorep -z ALL -f /myblobsdir 

The report might resemble the following: 

Glob Name File Name 

____________ _____________________________ 

MYGLOB /myblobsdir/MYGLOB 

REPORT_CHART /myblobsdir/REPORT_CHART 

ARCHIVED_DATA /myblobsdir/ARCHIVED_DATA 

JOB_SNAPSHOT /myblobsdir/JOB_SNAPSHOT 

This example generates a report that downloads the contents of all global blobs to the 

location /myblobsdir as text data: 

autorep -z ALL -f /myblobsdir -a 

The report might resemble the following: 

Glob Name File Name 

___________ __________________________________ 

MYGLOB /myblobsdir/MYGLOB.txt 

REPORT_CHART /myblobsdir/REPORT_CHART.txt 

ARCHIVED_DATA /myblobsdir/ARCHIVED_DATA.txt 

JOB_SNAPSHOT /myblobsdir/JOB_SNAPSHOT.txt