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In September 2018, IBM introduced a fresh product, IBM Db2 AI for z/OS. This synthetic intelligence engine monitors statistics entry patterns from executing SQL statements, uses computing device discovering algorithms to rule upon most fulfilling patterns and passes this counsel to the Db2 query optimizer for utilize by means of subsequent statements.laptop getting to know on the IBM z Platform
In may moreover of 2018, IBM announced version 1.2 of its machine gaining information of for z/OS (MLz) product. here's a hybrid zServer and cloud software suite that ingests efficiency data, analyzes and builds models that symbolize the fitness repute of various indications, monitors them over time and provides true-time scoring capabilities.
a few elements of this product providing are aimed at assisting a community of model builders and managers. for instance:
This machine getting to know suite become at first geared toward zServer-based analytics functions. one of the first obvious choices become zSystem efficiency monitoring and tuning. outfit management Facility (SMF) data that are instantly generated by the working outfit supply the raw statistics for outfit aid consumption comparable to censorious processor usage, I/O processing, reminiscence paging and so on. IBM MLz can assemble and store these records over time, and build and train models of device behavior, ranking those behaviors, determine patterns no longer effortlessly foreseen by means of people, enlarge key efficiency warning signs (KPIs) and then feed the mannequin outcomes returned into the device to gain an upshot on system configuration changes that can enrich performance.
The next step was to implement this suite to anatomize Db2 efficiency statistics. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) reply template, applies the computing device studying know-how to Db2 operational data to gain an realizing of Db2 subsystem fitness. it might dynamically build baselines for key performance symptoms, supply a dashboard of these KPIs and provides operational personnel true-time insight into Db2 operations.
while regularly occurring Db2 subsystem efficiency is a vital ingredient in middling utility health and performance, IBM estimates that the DBA aid cadaver of workers spends 25% or greater of its time, " ... fighting access route issues which antecedent efficiency degradation and service gain an upshot on.". (See Reference 1).AI involves Db2
agree with the plight of modern DBAs in a Db2 ambiance. In trendy IT world they gain to assist one or extra titanic data purposes, cloud application and database services, utility setting up and configuration, Db2 subsystem and application performance tuning, database definition and administration, catastrophe healing planning, and greater. question tuning has been in being due to the fact the origins of the database, and DBAs are continually tasked with this as neatly.
The coronary heart of query route analysis in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to access the statistics, reviews the places of the objects to exist accessed and develops an inventory of candidate information entry paths. These entry paths can comprehend indexes, table scans, numerous table exist participate of strategies and others. within the records warehouse and massive records environments there are usually further selections attainable. One of those is the being of summary tables (now and again called materialized query tables) that comprehend pre-summarized or aggregated information, for that intuition enabling Db2 to withhold away from re-aggregation processing. a different option is the starjoin entry path, middling in the data warehouse, where the order of desk joins is changed for efficiency explanations.
The Optimizer then studies the candidate access paths and chooses the access path, "with the bottom can charge." cost in this context means a weighted summation of resource usage including CPU, I/O, memory and other substances. ultimately, the Optimizer takes the lowest saturate access route, retailers it in memory (and, optionally, in the Db2 listing) and begins access direction execution.
massive statistics and records warehouse operations now encompass software suites that enable the traffic analyst to utilize a graphical interface to build and manipulate a miniature facts mannequin of the facts they necessity to analyze. The applications then generate SQL statements according to the clients’ requests.
The issue for the DBA
so as to enact respectable analytics for your numerous information shops you want a superb figuring out of the statistics requirements, an realizing of the analytical functions and algorithms attainable and a excessive-performance records infrastructure. regrettably, the quantity and placement of statistics sources is increasing (both in dimension and in geography), records sizes are transforming into, and purposes proceed to proliferate in number and complexity. How should quiet IT managers lead this ambiance, exceptionally with probably the most experienced and mature cadaver of workers nearing retirement?
be mindful additionally that a big participate of reducing the replete can saturate of ownership of those methods is to collect Db2 purposes to shun sooner and greater efficaciously. This constantly translates into using fewer CPU cycles, doing fewer I/Os and transporting less statistics across the community. because it's often tricky to even identify which applications could benefit from performance tuning, one method is to automate the detection and correction of tuning concerns. here's the station computer discovering and synthetic intelligence will moreover exist used to terrific impact.Db2 12 for z/OS and synthetic Intelligence
Db2 edition 12 on z/OS makes utilize of the computing device gaining information of amenities mentioned above to collect and store SQL query textual content and entry route details, as well as precise efficiency-related ancient information such as CPU time used, elapsed instances and influence set sizes. This offering, described as Db2 AI for z/OS, analyzes and outlets the information in computer learning models, with the mannequin analysis consequences then being scored and made purchasable to the Db2 Optimizer. The subsequent time a scored SQL observation is encountered, the Optimizer can then utilize the mannequin scoring information as enter to its access path option algorithm.
The upshot should exist a reduction in CPU consumption because the Optimizer makes utilize of mannequin scoring input to choose improved entry paths. This then lowers CPU prices and speeds application response instances. a significant competencies is that the utilize of AI utility does not require the DBA to gain statistics science information or abysmal insights into question tuning methodologies. The Optimizer now chooses the premiere entry paths based mostly now not best on SQL query syntax and information distribution statistics however on modelled and scored historic performance.
This may moreover exist specifically indispensable if you withhold information in assorted locations. as an example, many analytical queries in opposition t titanic statistics require concurrent access to determined statistics warehouse tables. These tables are often referred to as dimension tables, and they contain the facts features usually used to manipulate subsetting and aggregation. for instance, in a retail environment accept as accurate with a table known as StoreLocation that enumerates each save and its location code. Queries towards withhold sales records might moreover want to aggregate or summarize income by using location; hence, the StoreLocation desk might exist used by passage of some big data queries. during this atmosphere it's middling to grasp the dimension tables and copy them always to the titanic statistics application. in the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).
Now consider about SQL queries from each operational purposes, data warehouse clients and big statistics traffic analysts. From Db2's standpoint, bar not a bit these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should quiet certainly exist directed to entry the StoreLocation table within the warehouse. on the other hand, the query from the company analyst in opposition t huge data tables should quiet probably access the replica of the table there. This outcomes in a proliferations of information entry paths, and more toil for the Optimizer. fortuitously, Db2 AI for z/OS can give the Optimizer the assistance it must invent smart access direction choices.the passage it Works
The sequence of hobbies in Db2 AI for z/OS (See Reference 2) is often privilege here:
There are moreover quite a lot of consumer interfaces that supply the administrator visibility to the popularity of the amassed SQL observation efficiency facts and mannequin scoring.abstract
IBM's machine studying for zOS (MLz) providing is being used to super upshot in Db2 edition 12 to enrich the performance of analytical queries in addition to operational queries and their associated applications. This requires management consideration, as you necessity to investigate that your company is prepared to consume these ML and AI conclusions. How will you measure the fees and advantages of using machine discovering? Which IT serve group of workers necessity to exist tasked to reviewing the outcome of mannequin scoring, and maybe approving (or overriding) the outcomes? How will you overview and justify the assumptions that the software makes about entry direction decisions?
In different words, how neatly enact you know your facts, its distribution, its integrity and your latest and proposed entry paths? this will determine the station the DBAs spend their time in aiding analytics and operational utility efficiency.
# # #
John Campbell, IBM Db2 wonderful EngineerFrom "IBM Db2 AI for z/OS: enhance IBM Db2 application efficiency with laptop getting to know"https://www.worldofdb2.com/routine/ibm-db2-ai-for-z-os-increase-ibm-db2-utility-performance-with-ma
Db2 AI for z/OShttps://www.ibm.com/help/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html
DBAs and builders working with IBM DB2 regularly utilize IBM records Studio. Toad DBA Suite for IBM DB2 LUW complements facts Studio with advanced features that invent DBAs and developers a lot more productive. How can Toad DBA Suite for IBM DB2 LUW advantage your company? download the tech quick to discover.download PDF
download the authoritative e-book: Cloud Computing 2019: the usage of the Cloud for competitive competencies
See the whole checklist of computing device discovering optionsfinal analysis
RapidMiner may moreover now not gain the identify focus of AWS or Google, nonetheless it is a comprehensive data science platform. It aids groups in exploring, mixing and cleansing statistics, designing and refining predictive models through machine discovering and managing deployments. For organizations looking for a robust, expansive ML toolset, RapidMiner bears exploring.
RapidMiner uses a unified interface to manipulate numerous projects although a graphical drag-and-drop strategy. It offers pre-described computer getting to know libraries however moreover incorporates a lot of third-party libraries. This includes a whole bunch of add-ons encompassing computer studying, textual content analytics, predictive modeling, automation and manner manage.
This produces a quick classification and regression analysis system for both supervised and unsupervised gaining information of. The solution moreover helps split and go-validation methods that enhance the accuracy of predictive models. both Gartner and Forrester rank RapidMiner as a “leader.” The dealer additionally earned a Gartner consumer’s option 2018 award.Product Description
RapidMiner strategies information science and desktop gaining information of from a holistic viewpoint and presents a big number of outfit to manipulate myriad projects. The platform helps bar not a bit indispensable open supply facts science formats and provides greater than 60 connectors to control structured, unstructured and numerous sorts of massive information.https://o1.qnsr.com/log/p.gif?;n=203;c=204660772;s=9478;x=7936;f=201812281334210;u=j;z=TIMESTAMP;a=20403954;e=i
RapidMiner boasts that it presents more than 1,500 desktop getting to know and statistics prep functions, and it supports greater than forty info forms, including SAS, ARFF, Stata and by passage of URL. It helps NoSQL, MongoDB and Casandra, and its Radoop product extends information environments into the open supply Hadoop space.
This makes it practicable to generate and re-use current R and Python code, and mingle and recombine current modules with fresh extensions and modules. The platform moreover connects to foremost cloud storage functions similar to Amazon S3 and Dropbox. It writes to Qlik QVX or Tableau TDE files.Overview and lines person Base
facts scientists, developers, traffic analysts and citizen statistics scientists.Interface
Graphical user interface.Scripting Languages supported
Python, R and RapidMiner Studiocodecs Supported
more than 40 file varieties together with SAS, ARFF, Stata, and by means of URL. provides wizards for Microsoft surpass and access, CSV, and database connections. presents access to NoSQL databases MongoDB and Cassandra.Integration
guide for bar not a bit JDBC database connections together with Oracle, IBM DB2, Microsoft SQL Server, MySQL, Postgres, Teradata, Ingres, VectorWise, and others.Reporting and Visualization
in-built visualization tools. extensive logging capabilities.Pricing
$2,500 per user annually for the petite version (one hundred,000 facts rows and a pair of ratiocinative processors), $5,000 per consumer yearly for the medium edition (1,000,000 records rows and 4 ratiocinative processors) and $10,000 per person yearly for unlimited entry.RapidMiner Overview and features at a glance:
supplier and lines
ML focal point
enormously computerized ML platform ideal for businesses aiming to utilize machine getting to know commonly.
Key features and capabilities
presents greater than 1,500 computing device discovering and facts prep services, and it helps more than 40 files forms. Connects to Amazon S3 and Dropbox.
among the highest rated data science and ML options. clients describe it as effectual and “revolutionary” notwithstanding there are complaints concerning the necessity of GPU help.
Pricing and licensing
Tiered pricing ranging from $2,500 per consumer per year to upwards of $10,000 per consumer per 12 months.
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I’ve just completed IBM DB2 for Linux, Unix and Windows (LUW) coverage here on utilize The Index, Luke as preparation for an upcoming training I’m giving. This blog post describes the major differences I’ve establish compared to the other databases I’m covering (Oracle, SQL Server, PostgreSQL and MySQL).Free & Easy
Well, let’s visage it: it’s IBM software. It has a pretty long history. You would probably not await that it is smooth to install and configure, but in fact: it is. At least DB2 LUW Express-C 10.5 (LUW is for Linux, Unix and Windows, Express-C is the free community edition). That might exist another surprise: there is a free community edition. It’s not open source, but it’s free as in free beer.No smooth Explain
The first problem I stumbled upon is that DB2 has no smooth passage to parade an execution plan. No kidding. Here is what IBM says about it:
Explain a statement by prefixing it with interpret device for
This stores the execution device in a set of tables in the database (you’ll necessity to create these tables first). This is pretty much fancy in Oracle.
Display a stored interpret device using db2exfmt
This is a command line tool, not something you can plunge from an SQL prompt. To shun this tool you’ll necessity shell access to a DB2 installation (e.g. on the server). That means, that you cannot utilize this tool over an regular database connection.
There is another command line tool (db2expln) that combines the two steps from above. Apart from the fact that this procedure is not exactly convenient, the output you collect an ASCII art:Access Plan: ----------- Total Cost: 60528.3 Query Degree: 1 Rows RETURN ( 1) Cost I/O | 49534.9 ^HSJOIN ( 2) 60528.3 68095 /-----+------\ 49534.9 10000 TBSCAN TBSCAN ( 3) ( 4) 59833.6 687.72 67325 770 | | 1.00933e+06 10000 TABLE: DB2INST1 TABLE: DB2INST1 SALES EMPLOYEES Q2 Q1
Please note that this is just an excerpt—the replete output of db2exfmt has 400 lines. Quite a lot information that you’ll hardly ever need. Even the information that you necessity bar not a bit the time (the operations) is presented in a pretty unreadable passage (IMHO). I’m particularly thankful that bar not a bit the numbers you survey above are not labeled—that’s really the icing that renders this “tool” totally useless for the occasional user.
However, according to the IBM documentation there is another passage to parade an execution plan: “Write your own queries against the interpret tables.” And that’s exactly what I did: I wrote a view called last_explained that does exactly what it’s appellation suggest: it shows the execution device of the last statement that was explained (in a non-useless formatting):Explain Plan ------------------------------------------------------------ ID | Operation | Rows | Cost 1 | recur | | 60528 2 | HSJOIN | 49535 of 10000 | 60528 3 | TBSCAN SALES | 49535 of 1009326 ( 4.91%) | 59833 4 | TBSCAN EMPLOYEES | 10000 of 10000 (100.00%) | 687 Predicate Information 2 - combine (Q2.SUBSIDIARY_ID = DECIMAL(Q1.SUBSIDIARY_ID, 10, 0)) combine (Q2.EMPLOYEE_ID = DECIMAL(Q1.EMPLOYEE_ID, 10, 0)) 3 - SARG ((CURRENT DATE - 6 MONTHS) < Q2.SALE_DATE) Explain device by Markus Winand - NO WARRANTY http://use-the-index-luke.com/s/last_explained
I’m pretty certain many DB2 users will bid that this presentation of the execution device is confusing. And that’s OK. If you are used to the passage IBM presents execution plans, just stick to what you are used to. However, I’m working with bar not a bit kinds of databases and they bar not a bit gain a passage to parade the execution device similar to the one shown above—for me this format is much more useful. Further, I’ve made a useful selection of data to display: the row import estimates and the predicate information.
You can collect the source of the last_explained view from here or from GitHub (direct download). I’m serious about the no warranty part. Yet I’d fancy to know about problems you gain with the view.Emulating Partial Indexes is Possible
Partial indexes are indexes not containing bar not a bit table rows. They are useful in three cases:
To preserve space when the index is only useful for a very petite fraction of the rows. Example: queue tables.
To establish a specific row order in presence of constant non-equality predicates. Example: WHERE x IN (1, 5, 9) ORDER BY y. An index fancy the following can exist used to avoid a sort operation:CREATE INDEX … ON … (y) WHERE x IN (1, 5, 9)
To implement unique constraints on a subset of rows (e.g. only those WHERE dynamic = 'Y').
However, DB2 doesn’t advocate a where clause for indexes fancy shown above. But DB2 has many Oracle-compatibility features, one of them is EXCLUDE NULL KEYS: “Specifies that an index entry is not created when bar not a bit parts of the index key contain the null value.” This is actually the hard-wired behaviour in the Oracle database and it is commonly exploited to emulate partial indexes in the Oracle database.
Generally speaking, emulating partial indexes works by mapping bar not a bit parts of the key (all indexed columns) to NULL for rows that should not discontinue up in the index. As an example, let’s emulate this partial index in the Oracle database (DB2 is next):CREATE INDEX messages_todo ON messages (receiver) WHERE processed = 'N'
The solution presented in SQL Performance Explained uses a office to map the processed rows to NULL, otherwise the receiver value is passed through:CREATE OR REPLACE FUNCTION pi_processed(processed CHAR, receiver NUMBER) RETURN NUMBER DETERMINISTIC AS BEGIN IF processed IN ('N') THEN recur receiver; ELSE recur NULL; discontinue IF; END; /
It’s a deterministic office and can thus exist used in an Oracle function-based index. This won’t toil with DB2, because DB2 doesn’t allow user defined-functions in index definitions. However, let’s first complete the Oracle example.CREATE INDEX messages_todo ON messages (pi_processed(processed, receiver));
This index has only rows WHERE processed IN ('N')—otherwise the office returns NULL which is not set aside in the index (there is no other column that could exist non-NULL). Voilà: a partial index in the Oracle database.
To utilize this index, just utilize the pi_processed office in the where clause:SELECT message FROM messages WHERE pi_processed(processed, receiver) = ?
This is functionally equivalent to:SELECT message FROM messages WHERE processed = 'N' AND receiver = ?
So far, so ugly. If you fade for this approach, you’d better necessity the partial index desperately.
To invent this approach toil in DB2 they necessity two components: (1) the EXCLUDE NULL KEYS clause (no-brainer); (2) a passage to map processed rows to NULL without using a user-defined office so it can exist used in a DB2 index.
Although the second one might seem to exist hard, it is actually very simple: DB2 can enact expression based indexing, just not on user-defined functions. The mapping they necessity can exist accomplished with regular SQL expressions:CASE WHEN processed = 'N' THEN receiver ELSE NULL END
This implements the very selfsame mapping as the pi_processed office above. recall that CASE expressions are first class citizens in SQL—they can exist used in DB2 index definitions (on LUW just since 10.5):CREATE INDEX messages_not_processed_pi ON messages (CASE WHEN processed = 'N' THEN receiver ELSE NULL END) EXCLUDE NULL KEYS;
This index uses the CASE expression to map not to exist indexed rows to NULL and the EXCLUDE NULL KEYS feature to prevent those row from being stored in the index. Voilà: a partial index in DB2 LUW 10.5.
To utilize the index, just utilize the CASE expression in the where clause and check the execution plan:SELECT * FROM messages WHERE (CASE WHEN processed = 'N' THEN receiver ELSE NULL END) = ?; Explain Plan ------------------------------------------------------- ID | Operation | Rows | Cost 1 | recur | | 49686 2 | TBSCAN MESSAGES | 900 of 999999 ( .09%) | 49686 Predicate Information 2 - SARG (Q1.PROCESSED = 'N') SARG (Q1.RECEIVER = ?)
Oh, that’s a titanic disappointment: the optimizer didn’t grasp the index. It does a replete table scan instead. What’s wrong?
If you gain a very close search for at the execution device above, which I created with my last_explained view, you might survey something suspicious.
Look at the predicate information. What happened to the CASE expression that they used in the query? The DB2 optimizer was smart enough rewrite the expression as WHERE processed = 'N' AND receiver = ?. Isn’t that great? Absolutely!…except that this smartness has just ruined my attempt to utilize the partial index. That’s what I meant when I said that CASE expressions are first class citizens in SQL: the database has a pretty generous understanding what they enact and can transform them.
We necessity a passage to apply their magic NULL-mapping but they can’t utilize functions (can’t exist indexed) nor can they utilize CASE expressions, because they are optimized away. Dead-end? Au contraire: it’s pretty smooth to fuddle an optimizer. bar not a bit you necessity to enact is to obfuscate the CASE expression so that the optimizer doesn’t transform it anymore. Adding zero to a numeric column is always my first attempt in such cases:CASE WHEN processed = 'N' THEN receiver + 0 ELSE NULL END
The CASE expression is essentially the same, I’ve just added zero to the RECEIVER column, which is numeric. If I utilize this expression in the index and the query, I collect this execution plan:ID | Operation | Rows | Cost 1 | recur | | 13071 2 | FETCH MESSAGES | 40000 of 40000 | 13071 3 | RIDSCN | 40000 of 40000 | 1665 4 | SORT (UNQIUE) | 40000 of 40000 | 1665 5 | IXSCAN MESSAGES_NOT_PROCESSED_PI | 40000 of 999999 | 1646 Predicate Information 2 - SARG ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL discontinue = ?) 5 - START ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL discontinue = ?) discontinue ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL discontinue = ?)
The partial index is used as intended. The CASE expression appears unchanged in the predicate information section.
I haven’t checked any other ways to emulate partial indexes in DB2 (e.g., using partitions fancy in more recent Oracle versions).
As always: just because you can enact something doesn’t exist substantive you should. This approach is so ugly—even more frightful than the Oracle workaround—that you must desperately necessity a partial index to justify this maintenance nightmare. Further it will discontinue working whenever the optimizer becomes smart enough to optimize +0 away. However, then you just necessity set aside an even more frightful obfuscation in there.INCLUDE Clause Only for Unique Indexes
With the comprehend clause you can add extra columns to an index for the sole purpose to allow in index-only scan when these columns are selected. I knew the comprehend clause before because SQL Server offers it too, but there are some differences:
In SQL Server comprehend columns are only added to the leaf nodes of the index—not in the root and offshoot nodes. This limits the repercussion on the B-tree’s depth when adding many or long columns to an index. This moreover allows to bypass some limitations (number of columns, total index row length, allowed data types). That doesn’t seem to exist the case in DB2.
In DB2 the comprehend clause is only convincing for unique indexes. It allows you to enforce the uniqueness of the key columns only—the comprehend columns are just not considered when checking for uniqueness. This is the selfsame in SQL Server except that SQL Server supports comprehend columns on non-unique indexes too (to leverage the above-mentioned benefits).
The NULLS FIRST and NULLS last modifiers to the order by clause allow you to specify whether NULL values are considered as larger or smaller than non-NULL values during sorting. Strictly speaking, you must always specify the desired order when sorting nullable columns because the SQL touchstone doesn’t specify a default. As you can survey in the following chart, the default order of NULL is indeed different across various databases:
Figure A.1. Database/Feature Matrix
In this chart, you can moreover survey that DB2 doesn’t advocate NULLS FIRST or NULLS LAST—neither in the order by clause no in the index definition. However, note that this is a simplified statement. In fact, DB2 accepts NULLS FIRST and NULLS last when it is in line with the default NULLS order. In other words, ORDER BY col ASC NULLS FIRST is valid, but it doesn’t change the result—NULLS FIRST is anyways the default. selfsame is accurate for ORDER BY col DESC NULLS LAST—accepted, but doesn’t change anything. The other two combinations are not convincing at bar not a bit and bow a syntax error.SQL:2008 FETCH FIRST but not OFFSET
DB2 supports the fetch first … rows only clause for a while now—kind-of impressive considering it was “just” added with the SQL:2008 standard. However, DB2 doesn’t advocate the offset clause, which was introduced with the very selfsame release of the SQL standard. Although it might search for fancy an capricious omission, it is in fact a very sapient waddle that I deeply respect. offset is the root of so much evil. In the next section, I’ll interpret how to live without offset.
Side node: If you gain code using offset that you cannot change, you can quiet activate the MySQL compatibility vector that makes circumscribe and offset available in DB2. comical enough, combining fetch first with offset is then quiet not practicable (that would exist touchstone compliant).Decent Row-Value Predicates Support
SQL row-values are multiple scalar values grouped together by braces to contour a single ratiocinative value. IN-lists are a common use-case:WHERE (col_a, col_b) IN (SELECT col_a, col_b FROM…)
This is supported by pretty much every database. However, there is a second, hardly known use-case that has pretty destitute advocate in today’s SQL databases: key-set pagination or offset-less pagination. Keyset pagination uses a where clause that basically says “I’ve seen everything up till here, just give me the next rows”. In the simplest case it looks fancy this:SELECT … FROM … WHERE time_stamp < ? ORDER BY time_stamp DESC FETCH FIRST 10 ROWS ONLY
Imagine you’ve already fetched a bunch of rows and necessity to collect the next few ones. For that you’d utilize the time_stamp value of the last entry you’ve got for the bind value (?). The query then just recur the rows from there on. But what if there are two rows with the very selfsame time_stamp value? Then you necessity a tiebreaker: a second column—preferably a unique column—in the order by and where clauses that unambiguously marks the station till where you gain the result. This is where row-value predicates approach in:SELECT … FROM … WHERE (time_stamp, id) < (?, ?) ORDER BY time_stamp DESC, id DESC FETCH FIRST 10 ROWS ONLY
The order by clause is extended to invent certain there is a well-defined order if there are equal time_stamp values. The where clause just selects what’s after the row specified by the time_stamp and id pair. It couldn’t exist any simpler to express this selection criteria. Unfortunately, neither the Oracle database nor SQLite or SQL Server understand this syntax—even though it’s in the SQL touchstone since 1992! However, it is practicable to apply the selfsame logic without row-value predicates—but that’s rather inconvenient and smooth to collect wrong.
Even if a database understands the row-value predicate, it’s not necessarily understanding these predicates generous enough to invent proper utilize of indexes that advocate the order by clause. This is where MySQL fails—although it applies the logic correctly and delivers the privilege result, it does not utilize an index for that and is thus rather slow. In the end, DB2 LUW (since 10.1) and PostgreSQL (since 8.4) are the only two databases that advocate row-value predicates in the passage it should be.
The fact that DB2 LUW has everything you necessity for convenient keyset pagination is moreover the intuition why there is absolutely no intuition to complain about the missing offset functionality. In fact I judge that offset should not gain been added to the SQL touchstone and I’m tickled to survey a vendor that resisted the prod to add it because its became participate of the standard. Sometimes the touchstone is wrong—just sometimes, not very often ;) I can’t change the standard—all I can enact is teaching how to enact it privilege and start campaigns fancy #NoOffset.
Figure A.2. Database/Feature Matrix
If you fancy my passage of explaining things, you’ll fancy my reserve “SQL Performance Explained”.
Chances are, you gain never heard of Amanda… in the sense of open source that is. And if you gain not heard of Amanda, then chances are you gain not heard of Zmanda either. I will interpret both, and I will give you my view of why it is indispensable for you to at least exist watchful of these products and their relation to data protection. Whether you should invest in either depends on many factors that will become transparent shortly.
Let's start with Amanda. Amanda is the most common open source data protection product in the market today, at least based on the number of free downloads: 250,000 or more. fancy most free downloads, these usually approach from universities -- both students and IT folks -- and scientific labs. But, they moreover comprehend individuals from corporations that are experimenting with open source. In a nutshell, Amanda is a client/server data protection software that runs on a Linux server (backup server) and protects clients that shun Windows, Linux or Unix (only a few variants at the moment). It was developed originally at the University of Maryland and then dropped into the world of open source. Since it was distributed to the open source community, hundreds of programmers gain contributed to its development, bug fixes and its general care and feeding. As a result, the usage of the product has continued to climb dramatically over the past few years.You can utilize Amanda for free. You can modify it and set aside it back in the ether for free. But, fancy bar not a bit open source software, if the software just stopped running in the middle of the night because your client application server was not yet supported, generous luck trying to collect support. Or anything else. Your best stake would exist to station your request on one of many Web sites where users and developers serve each other out.
But, unlike Linux operating systems (where there are companies fancy RedHat and SUSE, which is now Novell) or Linux-based databases (where there are companies fancy mySQL), Amanda did not gain a "for profit" sponsor until recently. In late 2005, a newly-formed company was charged with working to invent Amanda a more usable product that would exist able to advocate enterprises of bar not a bit sizes. In keeping with the open source model, Zmanda has grabbed leadership of this space and is feverishly encouraging additional programmers -- some internal to the company, but most belonging to other companies/organizations -- to enhance Amanda so it can effectively compete with Symantec NetBackup, EMC Networker, CommVault Galaxy, Tivoli and others that plunge in the enterprise-class data protection software category. Even within the last six months, Amanda has approach a long way. But, it moreover has a long passage to fade before I would consider it a replete member of this class. Should you therefore ignore it? No. However, the intuition I am writing this column is to invent you watchful that, under the privilege set of circumstances, Amanda is worth considering.
Enter Zmanda. The company has released a specific version of Amanda (two versions, actually) that they advocate under the classic open source subscription model. You pay only for subscription and advocate and not for the product itself, just fancy any other open source product. Of course, the whole thought is to charge it such that the total cost of ownership is significantly (as in one-half to one-fourth the cost) lower than other commercial products.
But before you jump into the fray, inquire yourself the following questions:
I am certain that as you search for into these options you will gain other questions that are specific to your organization's needs. Version 2.50 of Zmanda does gain advocate for Windows and Linux, but not for bar not a bit common flavors of Unix. It should advocate databases and other applications in the future but does not privilege now. It moreover lacks a GUI and does not yet advocate bar not a bit the fresh innovations that they gain seen in the world of disk advocate (like VTL and CDP). But, it does gain disk support. It moreover has some features that I wish they had in the other commercial offerings, fancy a non-proprietary data format and fancy having the faculty to enact a recovery without requiring the vendor's software. Of course, its Linux advocate is excellent.
In my view, existent innovation occurs when there is a monetary incentive and there is a discontinuity in the technology curve. That is why they gain seen the massive transformation in data protection software in the past five years. SATA was the technology that opened up opportunities that just were not available before. But, before that, one could invent a pretty reasonable controversy that data protection software from bar not a bit the major vendors had become pretty bloated, and the rate of innovation was very slow. Adding advocate for a fresh tape library does not import as innovation in my book. It is precisely at such times, when differentiation between vendors' products is low, that open source starts to invent a lot of sense. Thousands of programmers start developing and creating a simpler, less cumbersome product with adequate functionality for many companies that don't necessity it all. Also, they are cost-sensitive and fancy the freedom.
That is how mySQL and, of course, Linux itself got going. Now it is Zmanda. But unlike the other segments, data protection is now experiencing phenomenal innovation. So, Amanda's (and therefore, Zmanda's) challenge will exist to not only create the feeble tape-based functionality but moreover to add bar not a bit the fresh juicy disk-based functionality that is coming in waves currently. I suspect it is up for the challenge but at least exist watchful that there could exist a lag before you survey bar not a bit of these features.
It was bound to happen. If database, J2EE, server virtualization and security tools got an open source counterpart, how far behind could data protection be? If you gain simpler needs, cost is a major issue and you crave that freedom from the titanic vendor -- for whatever intuition -- then you should check out this fresh space. But my advice: enact not shun a production environment without the advocate that comes with Zmanda. Amanda may exist free, but she can exist distress without the support.
About the author: Arun Taneja is the founder and consulting analyst for the Taneja Group. Taneja writes columns and answers questions about data management and related topics.
In-DepthIT Skills Poised To Pay
Advances in mobility, cloud, titanic Data, DevOps and digital delivery, plus the shift to more rapid release cycles of software and services, are enabling businesses to become more agile. IT workforce research and analyst firm Foote Partners assesses the IT skills gap these trends are creating, their repercussion on salaries and where the claim for expertise is headed.
It's difficult to find an employer not struggling to approach up with a unique tech staffing model that balances three things: the urgencies of fresh digital innovation strategies, combating ever deepening security threats, and keeping integrated systems and networks running smoothly and efficiently. The staffing challenge has moved well beyond simply having to choose between contingent workers, full-time tech professionals, and a variety of cloud computing and managed services options (Infrastructure as a Service [IaaS], Platform as a Service [PaaS], Software as a Server [SaaS]). Over the next few years, managers will continue to exist tasked with leading a massive transformation of the technology and tech-business hybrid workforce to focus on quickly and predictably delivering a wide variety of operational and revenue-generating infrastructure solutions involving Internet of Things (IoT) products and services, titanic Data advanced analytics, cybersecurity, and fresh mobile and cloud computing capabilities. Consequently, tech professionals and developers must align their skills and interests accordingly to serve their employers meet existing and forthcoming digital transformation imperatives that are forcing deep, accelerated changes in technology organizations.
As cloud infrastructure becomes more capable of economically delivering performance and data at capacities and speeds once never imagined, organizations of bar not a bit sizes are seeking tech professionals and developers with the proper skills, knowledge, and competencies to create more agile and responsive environments.
At the selfsame time, they're grappling to ensure reliability of existing infrastructure where any amount of downtime is less acceptable than ever. Along with that is an onslaught of cybersecurity attacks occurring more frequently that gain many IT managers aphorism they can't find adequate labor to serve them protect their existing networks and endpoints. The latest reminder was in the spotlight following the most powerful denial of service (DoS) attack to date in late October resulting from unprotected endpoints on surveillance cameras. IoT, machine-to-machine communications and telematics gain introduced fresh complexities ranging from the necessity to better secure the devices and the delivery points to which they connect. Meanwhile, the growing IoT landscape is unleashing an exponential flood of fresh data from hundreds of millions of devices, and organizations necessity to blend their IT and operational systems and find people with titanic Data analytics skills to manipulate the cloud-based machine learning infrastructure that's now emerging. This generational shift in IT will set aside a premium on, or create a baseline requirement for, IT professionals willing to result the money and survey where their skills will exist most applicable. Whether you're a manager looking to ensure your staff can deliver on these changes or an IT professional deciding on a career direction, workforce requirements and customer expectations are changing.
If you're in the latter camp, it's indispensable to understand that the supply-and-demand aspect that drives compensation is moreover a touching target. IT pay has a long history of volatility and in 2016 they gain seen even sharper swings in those premiums. Based on hiring patterns, the following overriding trends will drive market claim for IT professionals who gain the experience, drive and skills to deliver solutions:
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