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World®
’16
Reducing	TCO	with	Datacom	
Compression	(Presspack)
Kevin	Shuma,	VP	Product	Management
CA	Technologies
MFX94S
MAINFRAME	AND	WORKLOAD	AUTOMATION
2 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
©	2016	CA.	All	rights	reserved.	All	trademarks	referenced	herein	belong	to	their	respective	companies.
The	content	provided	in	this CA	World	2016	presentation	is	intended	for	informational	purposes	only	and	does	not	form	any	type	of	
warranty. The information	provided	by	a	CA	partner	and/or	CA	customer	has	not	been	reviewed	for	accuracy	by	CA.	
For	Informational	Purposes	Only	
Terms	of	this	Presentation
3 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Abstract
Come	to	this	session	to	learn	how	the	CA	Datacom®	Presspack	
can	reduce	the	total	cost	of	ownership	for	CA	Datacom®	
environments.
CA	Datacom®	Presspack	is	an	optional	component	of	the	CA	
Datacom®	product	family	and	provides	high	performance	
compression	for	data	rows	stored	in	CA	Datacom®/DB	database	
tables.	
Kevin	Shuma
CA	Technologies
VP,	Product	
Management
4 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Agenda
WHAT	ARE	THE	BENEFITS/COSTS	OF	COMPRESSION?
NEW	ONLINE	COMPRESS	ABILITY	– TA24
EXAMPLE	OF	ONLINE	COMPRESS
BENCHMARK	IN	OUR	LAB
SUMMARY	OF	FINDINGS
1
2
3
4
5
5 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
What	are	the	benefits	of	compression?
§ A	compressed	data	block	typically	has	significantly	more	rows	
which	means
– Less	blocks	on	DASD	to	store	the	same	number	of	rows
– Better	data	buffer	reuse	which	reduces	IO	and	improves	performance
– Less	memory	required	to	place	tables	in	memory	(MRDF)
– Quicker	utility	processing	for	backups	and	loads	(less	IO)
Why	should	I	consider	compression?
6 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
What	are	the	benefits	of	compression?
§ Can	make	data	less	“readable”	by	non	CA	Datacom®	utilities	
like	TSO	Browse
§ Slowing	DASD	growth	and	multiple	extent	management
Some	other	Benefits	of	Using	Compression:
7 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
What	are	the	costs	of	compression?
§ Requires	a	data	access	outage	to	implement
§ Not	easily	removed	or	changed
§ Hard	to	switch	from	one	vendor	to	another	
§ Uses	expensive	general	purpose	processor	(GP	CPU)	
instructions	to	save	cheap	DASD
Why	I	Should	Avoid	Using	Compression
8 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Using	zIIP	for	Compression
§ zIIP	processors	
– Can	be	used	for	in-memory	processing	like	compression
– Can	only	be	used	for	code	you	own
§ Cannot	be	used	to	process	imbedded	user/vendor	code	
– Example:	Non-CA	compression	code	imbedded	in	MUF		
§ Datacom	compression	runs	on	the	zIIP	processor(s)	while	
reducing	the	IOs	which	run	on	General	Purpose	processor(s)		
– Effectively	trading	inexpensive	zIIP	CPU	for	expensive	GP	CPU		
Tipping	the	Balance	for	Using	Compression
9 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
New	Online	Compress	Ability	– TA24
§ Provides	the	user	the	ability	to	alter	a	table’s	compression	
algorithm	without	interrupting	data	access			
§ Avoids	a	costly	data	access	outage	to	implement	or	change	
compression
§ Compression/decompression	activity	runs	in	background	in	
MUF
– Utilizes	zIIP	processors	for	compression	processing
Capabilities	Without	Interrupting	User	Access
10 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
New	Online	Compress	Ability	– TA24
§ Fully	restart-able	across	failures	(lack	of	space,	MUF	or	LPAR)
– The	partially	compressed	data	remains	accessible
– Once	the	failure	issue	is	resolved,	the	Online	Compress	will	be	
restarted	and	run	to	completion
§ Process	can	be	stopped	(REQABORT)	
– Allows	user	to	reverse	or	change	compression	setting
– New	process	will	run	to	completion	and	reset	all	rows	to	new	selection
Fully	Restart-able	and	Recoverable
11 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
New	Online	Compress	– Data	Blocks
§ When	decompressing	a	table
– Rows	may	grow	and	additional	data	blocks	will	be	used	
§ When	compressing	a	table
– Rows	will	shrink	making	more	space	available	in	each	data	block
– Space	immediately	available	for	use	by	new	requests
§ To	complete	the	process	a	online	reorganization	is	
recommended	
– OLREORG	REFGROUP=0	provides	best	result	(DSOP	4/5)
§ May	require	a	data	area	extension	if	not	enough	empty	blocks	to	get	rolling
Data	Blocks	in-use	Will	be	Affected
12 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Example	of	Online	Compress
§ Sample	table	containing	1	million	rows
§ Uncompressed	data	rows	fill	62K	data	
blocks
§ After	compression	62K	data	blocks	still	
in	use	but	each	block	has	significant	
free	space
§ After	OLREORG	REFGROUP=00	data	
blocks	are	defragmented
Come	to	Resource	Center	for	a	Live	Demo
Before
62K	Full	Data	Blocks
After	TA24	62K	
Partially	Data	
Blocks
After	OLREORG	24.5K	
Full	Data	Blocks
13 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
DBUTLTY	DATASP	Report	(Before	TA24)
Shows	Data	Blocks,	Data	Bytes	and	Data	Rows	“IN-USE”	
1M	rows	stored	in	98%	of	the	available	bytes	and	99%	of	the	available	data	blocks	in	
the	5,250	track	dataset
62K	Data	Blocks
14 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Use	DDUPDATE	to	Update	CA	Datacom®	Datadictionary™	
and	Trigger	Online	Compression
One	million	rows	
compressed	in	2	
minutes	(elapsed)
15 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
DBUTLTY	DATASP	Report	(After	TA24)
Shows	Data	Bytes	Significantly	Less,	but	Data	Blocks	and	Rows	the	Same
1M	rows	stored	in	39%	of	the	available	bytes	and	99%	of	the	available	data	blocks	in	
the	5,250	track	dataset
62K	Partially	full	
Data	Blocks
16 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Use	DBUTLTY	Online	Reorganization	To		
One	million	rows	
reorganized	and	
defragmented	in	5	
minutes	(elapsed)
17 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
DBUTLTY	DATASP	Report	(After	TA24/OLREORG)
Shows	Number	of	Blocks	in-use	Dropped	Dramatically	(Reduced	by	60%)
Same	number	of	rows	stored	in	39%	of	the	bytes	and	40%	of	the	data	blocks	in	the	
5,250	track	dataset
24.5K	Full	Data	Blocks
18 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Comparing	the	Processing	Before/After	TA24	+	OLREORG
Sequential	Program	Processing	All	1M	Rows
Logical	work	
is	exactly	
the	same	
(Requests,	
Logical	
reads	and	
Writes).
Physical	
reads	
reduced		by	
64%.
19 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Lab	Benchmark	Comparing	CPU/IO	Consumption
READ	1M	Rows	Each	- 10	Consecutive	Processes
Logical	work	
is	exactly	
the	same	
(Requests,	
Logical	
reads	and	
Writes).
Small	
buffer	
pool
Large	
buffer	
pool
Uncompressed
DB	Compress
Presspack	Weak
Presspack	Strong
Presspack	Custom
Uncompressed
DB	Compress
Presspack	Weak
Presspack	Strong
Presspack	Custom
Reduced	Elapsed,	CPU	and	IO
Much	better	reduction	with	large	buffer	pools
20 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Lab	Benchmark	Comparing	CPU/IO	Consumption
READ	1M	Rows	Each	- 10	Consecutive	Processes
Large	
buffer	
pool	
w/MRDF
Uncompressed
DB	Compress
Presspack	Weak
Presspack	Strong
Presspack	Custom
Logical	work	
is	exactly	
the	same	
(Requests,	
Logical	
reads	and	
Writes).
Reduced	Elapsed,	CPU	and	IO
Best	reduction	with	large	buffer	pools	and	MRDF	covered
21 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Lab	Benchmark	Comparing	CPU/IO	Consumption
Update	100K	of	1M	Rows	Read	- 10	Consecutive	Processes
Large	
buffer	
pool
Large	
buffer	
pool	
w/MRDF
Uncompressed
DB	Compress
Presspack	Weak
Presspack	Strong
Presspack	Custom
Uncompressed
DB	Compress
Presspack	Weak
Presspack	Strong
Presspack	Custom
Logical	work	
is	exactly	
the	same	
(Requests,	
Logical	
reads	and	
Writes).
Reduced	Elapsed,	CPU	and	IO
Best	reduction	with	large	buffer	pools	and	MRDF	covered
22 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Small	
buffers
Large	
Buffers	
w/MRDF
CPU/IO	Consumption	Without	a	zIIP Processor
READ	1M	Rows	Each	- 10	Consecutive	Processes
Logical	work	
is	exactly	
the	same	
(Requests,	
Logical	
reads	and	
Writes).
Reduced	IO	
CPU	and	Elapsed	differences	depend	on	buffering
Best	reduction	with	large	buffer	pools	and	MRDF	covered
23 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
What	if	There	is	a	3rd Party	Compression					
MRDF	
w/Presspack
MRDF	w/3rd
party	
JOEPACK Do	not	use	3rd party	
compression	and	zIIP	
(SMPTASK	x,x,x,SRB )
24 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Summary
§ Online	Compression	(TA24)	removes	several	of	the	key	drawbacks	
of	compression	
– No	longer	requires	a	data	access	outage	to	implement
– Can	be	easily	removed	or	changed
– Easily	switch	from	3rd party	vendor	to	CA	
§ When	compression	(Presspack)	combined	with	zIIP	(SRB)	
processing,	the	TCO	tips	in	favor	of	Presspack (CA)	compression	
– Uses	cheaper	zIIP	(CPU)	instructions	and	saves	DASD,	IO	and	memory
25 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
One	Extra	Benefit	
Uncompressed	or	Light	Compress	Data	is	Readable
Uncompressed
DB	
Compress	
and	
Presspack	
Weak
Readable
26 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
One	Extra	Benefit	
Strong	and	Custom	Compression	Can	Make	Data	Unreadable
Presspack	
Strong
Presspack	
Custom
Not	
Readable
27 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Recommended	Sessions
SESSION	# TITLE DATE/TIME
MFX92S Strategy	and	Vision	for	CA	Datacom	and	CA	Ideal™ 11/16/2016	at	12:45	pm
MFX93S What’s	new	in	CA	Datacom	 11/16/2016	at	1:45	pm
MFX94S Reducing	TCO	with	Datacom	Compression	(Presspack) 11/16/2016	at	3:00	pm
MFX95SA Modernizing	the	CA	Datacom	data – SQL	Access	Part	I 11/16/2016	at	3:45	pm
MFX95SB Modernizing	the	CA	Datacom	data – SQL	Access	Part	II 11/16/2016	at	4:30	pm
MFX96S CA	Datacom/AD	Installation/Upgrade	and	Maintenance 11/17/2016	at	12:45	pm
MFX97S
CA	Datacom/AD	Report	Utilization,	and
information	gather	for	Support
11/17/2016	at	1:45	pm
MFX98S
Using	CA	SYSVIEW®	to	monitor	and	measure	your	CA	
Datacom	environment	– AD	and	DB
11/17/2016	at	3:00	pm
MFX99S Birds	of	a	Feather/Stump	the	Techie!	 11/17/2016	at	3:45	pm
28 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Questions?
29 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Stay	connected	at	communities.ca.com
Thank	you.
@CAWORLD					#CAWORLD ©	2016	CA.	All	RIGHTS	RESERVED.30 @CAWORLD					#CAWORLD
Mainframe	and	Workload	Automation
For	more	information	on	Mainframe	and	Workload	Automation,		
please	visit:	http://cainc.to/9GQ2JI

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