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within the new update of DB2, launched Friday, IBM has added a set of acceleration technologies, collectively code-named BLU, that promise to make the venerable database administration system (DBMS) more desirable acceptable for operating significant in-memory statistics analysis jobs. "BLU has big benefits for the analytic and reporting workloads," stated Tim Vincent, IBM's vp and chief know-how officer for counsel administration application.
Developed by the IBM analysis and construction Labs, BLU (a development code name that stood for massive records, Lightening quickly, ultra effortless) is a bundle of novel innovations for columnar processing, records deduplication, parallel vector processing and data compression.
The center of attention of BLU changed into to permit databases to be "memory optimized," Vincent spoke of. "it'll run in reminiscence, but you won't have to put every thing in memory." The BLU know-how can also get rid of the want for loads of hand-tuning of SQL queries to raise efficiency.faster data analysis
on account of BLU, DB2 10.5 may velocity facts analysis by way of 25 instances or greater, IBM claimed. This growth might eliminate the deserve to buy a separate in-reminiscence database—akin to Oracle's TimesTen—for speedy records analysis and transaction processing jobs. "We're now not forcing you from a value mannequin perspective to dimension your database so every thing matches in reminiscence," Vincent spoke of.
On the net, IBM supplied an illustration of how 32-core system the use of BLU technologies could execute a question in opposition t a 10TB records set in less than a 2nd.
"In that 10TB, you might be [probably] interacting with 25 percent of that information on daily operations. you'd only deserve to maintain 25 % of that statistics in reminiscence," Vincent observed. "you can buy these days a server with a terabyte of RAM and 5TB of solid state storage for under $35,000."
IBM's BLU acceleration know-how speeds DB2 queries against enormous information units.
also, using DB2 might cut the labor costs of operating a separate facts warehouse, on account that the pool of attainable database directors is frequently greater than that of facts warehouse consultants. In some circumstances, it may even function an easier-to-preserve option to the Hadoop records processing platform, Vincent referred to. among the many new technologies is a compression algorithm that outlets information in such a way that, in some instances, the information does not need to be decompressed earlier than being study. Vincent defined that the statistics is compressed in the order through which it is stored, which skill predicate operations, such as adding a where clause to a question, will also be carried out devoid of decompressing the dataset.
all over again-saving trick: the utility keeps a metadata table that lists the excessive and low key values for every records web page, or column of data. So when a question is accomplished, the database can verify to peer if any of the sought values are on the records page."If the page isn't in memory, they would not have to read it into reminiscence. if it is in reminiscence, they should not have to carry it throughout the bus to the CPU and burn CPU cycles examining all the values on the web page," Vincent noted. "That enables us to be a lot greater efficient on their CPU utilization and bandwidth."With columnar processing, a question can pull in precisely the selected columns of a database table, in preference to the entire rows, which might eat extra memory. "we now have come up with an algorithm that is awfully productive in opting for which columns and which ranges of columns you would are looking to cache in reminiscence," Vincent spoke of.
On the hardware facet, the utility comes with parallel vector processing capabilities, a way of issuing a single guide to distinctive processors the use of the SIMD (Single guideline diverse data) guideline set accessible on Intel and PowerPC chips. The software can then run a single query against as many columns because the system can area on a register. "The register is the ultimate memory utilization aspect of the gadget," Vincent stated.competitors rally
IBM is not alone in investigating new methods of cramming massive databases into the server memory. last week, Microsoft introduced that its SQL Server 2014 would also include a few ideas, at the same time known as Hekaton, to maximize using working reminiscence, in addition to a columnar processing technique borrowed from Excel's PowerPivot expertise.
Database analyst Curt Monash, of Monash analysis, has stated that with IBM's DB2 10.5 unencumber, Oracle now could be "now the only primary relational DBMS seller left without a true columnar story."
IBM itself is using the BLU components of DB2 10.5 as a cornerstone for its DB2 SmartCloud infrastructure as a provider (IaaS), so as to add computational heft for records reporting and evaluation jobs. it could actually additionally insert the BLU technologies into different IBM information store and analysis items, such as Informix.To touch upon this article and different PCWorld content, visit their fb web page or their Twitter feed.
IBM has created a neat new database feature for its DB2 database for Linux, Unix, and windows operating techniques on the way to hopefully make its means into the built-in DB2 for i database that resides inside the IBM i working device. For now, this BLU Accelerator feature, that can radically velocity up the sifting through statistics, is simply accessible for DB2 10.5 and handiest for reporting and analytics, but there's every intent to agree with massive Blue will put it on the IBM i and mainframe versions of its DB2 database and use it to support goose transaction processing.
Like different IT companies, IBM wants organizations to suppose that each little bit of information that they generate or compile from their methods or purchase from third events during working their company is constructive, and the intent is essential. This sells storage arrays, and in case you can make CEOs think this records is doubtlessly positive, then they're going to fork out the money to maintain it internal of a considerable number of sorts of records warehouses or Hadoop clusters for statistics at relaxation or in InfoSphere Streams programs for records and telemetry in action. there is large cash in them there large statistics hills, and with server virtualization pulling the rug out from underneath the server business during the past decade, hindering income growth, the funny element about these big facts jobs is that none of them are virtualized and based on the big quantities of records they need to take up every day, they maintain swelling like a batch of yeast.
IBM is not making any guarantees about bringing BLE Accelerator, that could goose analytics queries through between an element of eight and 25 instances while on the identical time reducing storage potential needs for information units due to columnar information compression, to different databases, but Tim Vincent, who's chief architect for DB2 on the Linux, Unix, and home windows structures, who's an IBM Fellow, and who's chief technology officer for IBM’s tips administration division, hinted pretty strongly. “We do plan on extending this,” Vincent said at the BLU Accelerator launch in early April, “and we're going to carry the know-how into new items going ahead.”
So what exactly is BLU Accelerator? smartly, it's loads of issues. First, BLU implements a new runtime this is embedded inner of the DB2 database and a new table classification that is used by means of that runtime. These BLU tables coexist with the common row tables in DB2, and have the identical schema and use storage and reminiscence the same way. The BLU tables orient information in columns as a substitute of the traditional row structured table used in relational databases, and this records is encoded in such a manner (the use of what Vincent called an approximate Huffman encoding algorithm) that has a further function whereby the statistics is kept so as so it can be searched even whereas it is compressed. The BLU Accelerator has a reminiscence paging structure in order that a whole database desk does not must reside in main memory to be processed, but the intention is to make use of the columnar structure to allow the database to be compressed enough so it may possibly live in main reminiscence and be plenty greater quickly searched. however again, it is not required, like some in-memory database administration programs, and you'll movement chunks of a BLU database into leading reminiscence as you should query it. The BLU Accelerator knows about dissimilar core processors and SIMD engines and vector coprocessors on chips, and it may take talents of these gadgets to compress and search information. The Actionable Compression algorithm, as IBM calls it, is patented and enables for records for use devoid of decompressing it, which is a neat trick. The accelerator characteristic can also do whatever thing called data skipping, which potential it will possibly evade processing inappropriate statistics in a desk to do a question.
right here’s the examine and contrast between the manner DB2 works now, with all of the snazzy aspects to increase its efficiency which have been delivered through the years, and the way the BLU Accelerator function works:
adequate, i am not a database professional or a comedian, however this is funny. The freaky thing about BLU Accelerator is that it does have database indexes. You don’t must do aggregates on the tables, you don’t ought to tune your queries or the database, and you don’t have to make any alterations to SQL or database schemes. “You just load the information and query it,” as Vincent mentioned on the launch of the product.
The intent that you don’t want a database index is that records is compressed so a BLU table can, often talking, dwell in reminiscence. Vincent observed that eighty percent of the information warehouses on the earth had 10 TB of means, so if you can use the Actionable Compression and get a 10X compression ratio, then you can fit the usual facts warehouse in a 1 TB memory footprint. however there are greater hints that velocity up those database queries, as you could see here:
once you have compressed the records so it all matches into main memory, you are taking skills of the indisputable fact that you have got equipped the statistics in columnar layout as an alternative of row structure. So, during this case, you place each and every of 10 years of information into 10 diverse columns every, for a total of 100 columns. And for those who are looking to search in 2010 handiest for a collection of the data, as the query above–locate the number of sale deals that the enterprise did in 2010–does, you then cut back that question down to 10 GB of the facts within the complete set. The information skipping feature during this case is aware of to search for revenue information, not different types of facts, so that reduces the statistics set all the way down to around 1 GB. The desktop you're the usage of to run this BLU Accelerator characteristic now not most effective has 1 TB of main reminiscence however 32 cores, so that you parallelize the question and destroy it up so 32 MB chunks of the statistics are partitioned and parceled out to every of the 32 cores and their memory segments. Now, use the vector processing means in an X86 or power processor, and you get round an element of 4 speedup in scanning the facts for the revenue facts. And the influence is that you can query a 10 TB desk in a second or less.
Sounds relatively useful, correct? So when do the other DB2s get it? We’ll are trying to discover.
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ARMONK, N.Y., June 26, 2013 /PRNewswire by means of COMTEX/ -- IBM IBM, +0.49% these days announced powerful client and enterprise companion aid for the new version of its DB2 database utility, now commonly purchasable. the new software -- which represents the work of tons of of IBM developers and researchers in labs around the globe -- provides game-changing expertise referred to as BLU Acceleration that makes it less difficult, greater not pricey and dramatically quicker to analyze big quantities of facts.
As groups face a flood of records generated by using computer systems, mobile devices, sensors and social networks, they're beneath unprecedented force to analyze a great deal greater statistics at faster speeds and reduce fees. BLU Acceleration allows clients to have an awful lot sooner access to key tips.
among the many organizations international which have skilled strong results from the brand new IBM application is the huge northern Europe financial institution Handelsbanken. "We had been very impressed with the efficiency and ease of BLU. They discovered that some queries executed an almost one hundred instances speedup with actually no tuning. They had been seeing average acceleration of seven.4 times, with some queries going from 28 seconds down to sub-second response time," stated Lennart Henang, IT Architect at Handelsbanken.
Yonyou application Co. in Beijing is a number one commercial enterprise administration application and cloud carrier provider. according to Jianbo Liu, IT efficiency manager at Yonyou, "ERP and accounting utility purposes run a lot of experiences. They used DB2 BLU Acceleration and noticed their studies run sooner by as much as 40 instances. This classification of technology is a great fit for Yonyou's massive facts Analytic capabilities."
"The remarks we're hearing from shoppers and companions illustrates that we're proposing an imaginative and strong yet standard solution that may ingest large quantities of information and observe insights from all this data at the point of have an effect on," observed Bob Picciano, accepted supervisor, IBM information administration. "IBM's work with beta consumers and internal checks exhibit large pace and ease. in one illustration, BLU Acceleration turned into shown to be 10 times sooner than an extra established in-reminiscence database system. Some queries that took 7 minutes were proven to have dropped to 8 milliseconds, due to the innovations in BLU Acceleration."
the brand new IBM DB2 10.5 with BLU Acceleration goals for analytics on the velocity of thought with a number of made-in-IBM-Labs advances to significantly speed analytic workloads for databases and facts warehouses:
-- Dynamic in-reminiscence technology that masses terabytes of facts in Random entry memory, which streamlines query workloads even when facts sets exceed the dimension of the reminiscence.
-- "Actionable Compression," which allows analytics to be carried out directly on compressed records without needing to decompress it - some consumers have mentioned as tons as 10 instances cupboard space discount rates.
-- An creative strengthen in database technology that permits DB2 to system each row-based and column-based mostly tables concurrently within the equal device. This allows for plenty faster evaluation of big amounts of statistics for faster decision-making.
-- The simplicity to permit purchasers access to blazing-fast analytics transparently to their purposes, with out the deserve to increase a separate layer of facts modeling or time ingesting records warehouse tuning
-- Integration with IBM Cognos enterprise Intelligence Dynamic Cubes to deliver step forward velocity and ease for reporting and analytics. companies can analyze key data and freely discover greater guidance quicker from distinct angles and perspectives to make greater recommended selections.
-- The means to take talents of both multi-core and single guide distinctive records (SIMD) points in IBM vigour and Intel x86 processors
"The complete thought at the back of DB2 with BLU Acceleration is definitely reasonably charming," observed Andrew Juarez, a lead database administrator at Coca Cola Bottling Co. Consolidated. "I basically admire the strategy of giving me all of the benefits of a columnar database in concord with a row-store inside the equal database. What IBM also has done it's so particular with BLU Acceleration is it permits us to carry potent efficiency, even if the whole facts set won't fit into reminiscence. that is critical because in a huge records world, I may now not be capable of fit all of my facts into memory, even with very excessive compression ratios. DB2 gives me a single solution for a essential enterprise intention: bring sooner analytics to their users."
"We moved from Oracle Database to DB2 in April 2008," Juarez brought. "earlier than moving to DB2, their database changed into 950 GB and sustained a 35 GB-per-month increase price. simply with the aid of moving to DB2, the boom expense slowed to fifteen GB/month. nowadays their database is smaller than it turned into in 2008. just when i assumed issues could not get any superior, BLU Acceleration came alongside."
Iqbal Goralwalla, head of DB2 Managed functions at Triton Consulting of Norwich, UK, mentioned, "i was rather anxious after I put in DB2 10.5 with BLU Acceleration on my Linux Intel server, which definitely does not have a large volume of RAM, nor does it have the newest processors. The consequences surprised me. My analytic workload ran forty five instances faster. here is because with BLU Acceleration, not handiest can the facts be larger than the quantity of obtainable RAM, but DB2 is additionally very beneficial at preserving the facts in memory and become performing the records analytics directly on compressed facts."
The breakthrough velocity and simplicity of BLU Acceleration is a complement to the present transactional performance management of DB2 on vigour gadget. DB2 takes capabilities of energy gadget's trade leading multi-threading, cache measurement and memory bandwidth to bring correct pace and processing effectivity for both transactional and analytics workloads.
For extra tips about IBM's massive data platform: http://www-01.ibm.com/software/statistics/bigdata/platform/product.html
For more information about BLU Acceleration: http://www-01.ibm.com/utility/statistics/db2/linux-unix-home windows/db2-blu-acceleration/
Media Contact: Steve Eisenstadt IBM Media members of the family 1-914-766-8009 firstname.lastname@example.org
Copyright (C) 2013 PR Newswire. All rights reserved
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With the launch of DB2 10.1, Big Blue is adding a slew of new features that make DB2 more useful for modern, big-data workloads.
Depending on how you want to count it, IBM is either the world's number-two or number-three seller of database management systems, and it has a lot of secondary systems and services business that are driven off its DB2 databases.
Notice that they said DB2 databases. IBM has three different DB2s, not just one. There's DB2 for the mainframe, DB2 for its midrange IBM i (formerly OS/400) platform, and DB2 for Linux, Unix, and Windows platforms.
It is the latter one, known sometimes as DB2 LUW, that was revved up to the 10.1 release level on Tuesday. Concurrent with the database upgrade, IBM is also upgrading its InfoSphere Warehouse – a superset of DB2 designed for data warehousing and OLAP serving – to the 10.1 level.
At a very high level, explains Bernie Spang, director of product strategy for database software and systems at IBM, the DB2 10.1 release is focused on two things: the challenge of coping with big data, and automating more of "the drudgery of the mechanics of the data layer" in applications.
The update to DB2 and InfoSphere Warehouse, which both ship on April 30, is the culmination of four years of development by hundreds of engineers working around the globe from IBM's software labs. The new database also has several performance enhancements, a new data-compression method, and increased compatibility with Oracle databases to help encourage Oracle shops to make the jump.
On the big-data front, IBM has juiced the connector that links DB2 to Hadoop MapReduce clusters running the Hadoop Distributed File System (HDFS). Spang says that the prior Hadoop connector was "rudimentary", and so coders went back to the drawing board and created a much better one that allows for data warehouses to more easily suck in data from and spit out data to Hadoop clusters, with less work on the part of database admins.
IBM's DB2 10 versus InfoSphere Warehouse 10 (click to enlarge)
The new DB2 also supports the storing of graph triples, which are used to do relationship analytics, or what is sometimes called graph analytics.
Rather than looking through a mountain of data for specific subsets of information, as you do in a relational database or a Hadoop cluster, graph analytics walks you through all of the possible combinations of data to see how they are connected. The links between the data are what is important, and these are usually shown graphically using wire diagrams or other methods – hence the name graph analysis.
Graph data is stored in a special format called Resource Definition Framework (RDF), and you query a data store with this data using a query language called SPARQL.
The Apache Jena project is a Java framework for building semantic web applications based on graph data, and Apache Fuseki is the SPARQL server that processes the SPARQL queries and spits out the relationships so they can be visualized in some fashion. (Cray's new Urika system, announced in March, runs this Apache graph analysis stack on top of a massively multithreaded server.)
Just like they imported objects and XML into the DB2 database so they could be indexed and processed natively, IBM is now bringing in the RDF format so that graph triples can be stored natively.
As IBM explains it – not strictly grammatically, to some English majors – a triple has a noun, a verb, and a predicate, such as Tim (noun) has won (verb) the MegaMillions lottery (predicate). You can then query all aspects of a set of triples to see who else has won MegaMillions – a short list, in this case.
In tests among DB2 10.1 early adopters, applications that used these graph triples ran about 3.5 times faster on DB2 than on the Jena TDB data store (short for triple database, presumably) with SPARQL 1.0 hitting it for queries.
DB2 10.1 for Linux, Unix, and Windows platforms also includes temporal logic and analysis functions that allow it to do "time travel queries" – functions that IBM added to the mainframe variant of DB2 last year. By now supporting native temporal data formats inside the database, you can do AS OF queries in the past, present, and future across datasets without having to bolt this onto the side of the database.
"This dramatically reduces the amount of application code to do bi-temporal queries," says Spang, and you can do it with SQL syntax, too. You can turn time travel query on or off for any table inside the DB2 database to do historical or predictive analysis across the data sets. RDF file format and SPARQL querying are available across all editions of DB2 10.1.
Like other database makers, IBM is fixated on data compression techniques not only to reduce the amount of physical storage customers need to put underneath their databases, but also to speed up performance. With DB2 9.1, IBM added table compression, and with the more recent DB2 9.7 from a few years back, temporary space and indexes were compressed.
With DB2 10.1, IBM is adding what it calls "adaptive compression", which means applying data row, index, and temp compression on the fly as best suits the needs of the workload in question.
In early tests, customers saw as much as an 85 to 90 per cent reduction in disk-capacity requirements. Adaptive compression is built into DB2 Advanced Enterprise Server Edition and Enterprise Developer Edition, but is an add-on for an additional fee for Enterprise Server Edition.Performance boosts, management automation
On the performance front, IBM's database hackers have tweaked the kernel of the database to make better use of the parallelism in the multicore, multithreaded processors that are common today, with specific performance enhancements for hash joins and queries over star schemas, queries with joins and sorts, and queries with aggregation.
Out of the box, IBM says that DB2 10.1 will run up to 35 per cent faster than DB2 9.7 on the same iron. With all of the data compression turned on, many early customers are seeing a factor of three better performance from their databases. Which means – sorry, Systems and Technology Group – many DB2 customers are going to be able to get better performance without having to buy new iron.
On the management front, DB2 now has integrated workload management features that can cap the percentage of total CPU capacity that DB2 is allowed to consume, with hard limits and soft limits across multiple CPUs that are sharing capacity. You can also prioritize important DB2 workloads with different classes of service level agreements.
Database indexes now have new features such as jump scan, which optimizes buffer usage in the underlying system and cuts down on the CPU cycles that DB2 eats, as well as smart prefetching of index and data to boost the performance of the database, much as L1 caches in chips do for their processors.
DB2 now also has a multi-temperature data management feature that knows the difference between flash-based SSDs, SAS RAID, SATA RAID, and tape or disk archive, and can automagically move database tables that are hot, warm, cold, and downright icy to the right device.
Access control is a big deal, and DB2 10.1 now sports fine-grained row and column access controls so each user coming into a system can be locked out of any row or column of data. Now, employees only see the data they need to know, and you don't have to partition an application into different classes of users. You just do it at the user level based on database policies. This feature masks just the data you are not supposed to see.
IBM continues to ramp up its compatibility with Oracle's PL/SQL query language for its eponymous databases, and says that with the 10.1 release, early access users are seeing an average of 98 per cent compatibility for Oracle PL/SQL queries running against DB2. That's not 100 per cent, but it is getting closer.
Finally, as far as big features go, the other new one is called "continuous data ingest", which allows for external data feeds to continuously pump data into the database, or for the database to continuously pump into the data warehouse, without interrupting queries running on either box. This ingesting relies on bringing the data into the database and warehouse in a parallel fashion, with multiple connections, but exactly how it works is not clear to El Reg as they go to press. It seems a bit like magic.
DB2 Express-C is free and has the time travel feature; it is capped at two processor cores and 4GB of main memory. DB2 Express adds the row and column access control, label access control (an existing feature) high availability clustering features (new with this release), and has a memory cap of 8GB and can run across four processor cores; it costs $6,490 per core.
Workgroup Server boosts the cores to 16 and the memory to 64GB, and doesn't have the HA features. Enterprise Server has the multi-temperature data management feature and costs $30,660 per core. The top-end Advanced Enterprise Server has all the bells and whistles, including optimizations and tools to make DB2 play better in a data warehouse. Pricing for the Workgroup Server and Advanced Enterprise Server were not available at press time. ®
Sponsored: Becoming a Pragmatic Security Leader
Environment : Linux , DB Version : 10.5Configure the Server to use SSL
Lets understand the requirement here. They need the DB Server to accept connections from a new port which uses SSL. So they need to open a new service to accept SSL connections. One part of this task is authentication (which can be done also via certificates) and another part is the encrypted connection that protects the communication between server and client.
GSKit package is used for key generations. This is automatically installed when DB2 is installed. The default path is (For Linux the default path is /opt/ibm/db2/V11.1/gskit/bin/).
rule : Run all commands as instance owner.
Ok now lets start ….
note : if the LIBPATH is set correctly, no need to specify a path when running gsk8capicmd_64.
Command gsk8capicmd_64 is used for management of CA certificates. In their command they used the following options:
The -stash option creates a stash file at the same path as the key database, with a file extension of .sth. At instance start-up, GSKit uses the stash file to obtain the password to the key database.
2. The next step is to create a certificate for the key database. Here, I will create a self-signed certificate with a label mylabel.
/home/db2inst2/sqllib/gskit/bin/gsk8capicmd_64 -cert -create -db “server.kdb” -pw “Passw0rd” -label “mylabel” -dn “CN=testcompany” -size 2048 -sigalg SHA256_WITH_RSA
The following options are used:
3. Extract the certificate you just created to a file, so that you can distribute it to computers running clients that will be establishing SSL connections to your Db2 server./home/db2inst2/sqllib/gskit/bin/gsk8capicmd_64 -cert -extract -db “server.kdb” -pw “Passw0rd” -label “mylabel” -target “server.arm” -format ascii -fips
at this stage your directory will have the below set of files,
server.rdb, server.crl, server.sth, server.kdb, server.arm
To display the certificate, issue the following command:/home/db2inst2/sqllib/gskit/bin/gsk8capicmd_64 -cert -details -db “server.kdb” -pw “Passw0rd” -label “mylabel”
You will be needing the above files later… now lets move into configuring the DataBase to create a new SSL service.
4. Changes in DB2 Server Configurations To set up your Db2 server for SSL support, log in as the Db2 instance owner and set the following configuration parameters and the DB2COMM registry variable.a. Set the ssl_svr_keydb configuration parameter to the fully qualified path of the key database file. (.kdb file is used from the above 5 files created.Author assumes that you have created the keys in this path : /home/db2inst2/cert/)
db2 update dbm cfg using SSL_SVR_KEYDB /home/db2inst2/cert/server.kdboutput :DB20000I The UPDATE DATABASE MANAGER CONFIGURATION command completedsuccessfully.
b. Set the ssl_svr_stash configuration parameter to the fully qualified path of the stash file. (.sth file is used from the above 5 files created.Author assumes that you have created the keys in this path : /home/db2inst2/cert/)db2 update dbm cfg using SSL_SVR_STASH /home/db2inst2/cert/server.sthOutput :DB20000I The UPDATE DATABASE MANAGER CONFIGURATION command completedsuccessfully.
c. Set the ssl_svr_label configuration parameter to the label of the digital certificate of the server, which you added in Step 1. If ssl_svr_label is not set, the default certificate in the key database is used. If there is no default certificate in the key database, SSL is not enabled.db2 update dbm cfg using SSL_SVR_LABEL mylabel
d. The SSL connections require a separate port. It can be defined as a service name or port number. The service name needs to be defined in /etc/services. vi /etc/services file and add a new service name for SSL port.
db2cs_db2inst2 50002/tcpeg: make sure the service name and port is different from the existing port, db2c_db2inst2 50001/tcp db2cs_db2inst2 50002/tcp
e. The new service name is db2cs_db2inst2, port 50002, protocol TCP. This parameter is also required to enable SSL connections.db2 update dbm cfg using SSL_SVCENAME db2cs_db2inst2
OutPut : DB20000I The UPDATE DATABASE MANAGER CONFIGURATION command completedsuccessfully.
f. Add the value SSL to the DB2COMM registry variable. db2set -i db2inst2 DB2COMM=SSL
g. Ensure to enable both TCP/IP and SSL communication protocols for the DB Instance. If you are planning to use only one, then no need to add both. db2set -i db2inst2 DB2COMM=SSL,TCPIPDone.
Just to be on the safe side, validate you configs using the below command.db2 get dbm cfg|grep SSL SSL server keydb file (SSL_SVR_KEYDB) = /home/db2inst2/cert/server.kdb SSL server stash file (SSL_SVR_STASH) = /home/db2inst2/cert/server.sth SSL server certificate label (SSL_SVR_LABEL) = mylabel SSL service name (SSL_SVCENAME) = db2cs_db2inst2 SSL cipher specs (SSL_CIPHERSPECS) = SSL versions (SSL_VERSIONS) = SSL client keydb file (SSL_CLNT_KEYDB) = SSL client stash file (SSL_CLNT_STASH) =
5. Stop and ReStart the DB. 6. Validate if the DB is started with multiple ports. netstat -tap|grep db2tcp 0 0 *:db2c_db2inst2 *:* LISTEN 23682/db2sysc 0tcp 0 0 *:db2cs_db2inst2 *:* LISTEN 23682/db2sysc 0
IBM last week unveiled the version 7.3 release of its Optim suite of tools, which helps organizations to archive data and prepare data for testing. The new version adds support for the latest server operating systems and database. IBM also launched Optim Application Retirement, for JD Edwards EnterpriseOne and Siebel applications that are getting a little long in the tooth.
Just because an organization is no longer actively using an enterprise application, it does not mean the application can be completely disregarded. For one thing, the organization may need to access the data contained within the application and its database. Also, the organization may need to maintain the data in a legally compliant manner.
IBM can help in these situations with a version of its Optim data archiving utility specifically designed for retiring old applications. Optim Application Retirement helps in three main areas, including consolidating the data within old applications, enabling access to the data through standard reporting tools, and addressing information lifecycle management and compliance requirements.
IBM previously offered a general purpose version of Optim for use in retiring old enterprise applications. With the launch of Optim Application Retirement, it now provides predefined models and templates for achieving retirement-related tasks within the EnterpriseOne and Siebel data structures.
IBM also updated the rest of its Optim suite, which includes the version 7.3 releases of Optim Data Growth and Optim Test Management solutions, and new releases of related tools.
With version 7.3 IBM supports the latest releases of the major databases, including SQL Server 2008, DB2 LUW 9.5 and 9.7, Oracle 11g and 11g R2, and DB2 z/OS 10.1. (DB2/400 is not supported; companies running EnterpriseOne on IBM i must first load the data into DB2 LUW to use Optim, according to IBM instructions.) Optim 7.3 also now supports Unicode on Informix, and gains various performance enhancements resource estimators, and data loading enhancements.
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