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PostgreSQL - The Database for Industry 4.0 and IOT

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so 1st thing where mind I'm using past grows grows the rings around 1996 I was using it 1st with PHB so I was young and in the the money's by the essentially been using PostgreSQL along i've used heightened I joined applied and human communities something around 2003 with the Europe ideational and I form my own company the clearing
other databases and girl staff and put into exile and due to my involvement you in the Python community and later in the past community I was spotted by 2nd quadrant which is a global pulse grows growth support and development company and invited to run the German affiliation offset quadrant now we're talking about past grass grows a database for Internet of Things and industry fall about serial so all wild people still streaming in I will spend some time on discussing what's behind those terms a given approach and make clear what we're focusing on that Internet of Things I found very interesting graphic which is much better than those bullet points it started out with tracking everything on the big peak rate is a don't have furor entrance badges half an hour off Aidid entrance batch so you can scan it the idea is you put computers in to everything that's everywhere it started out with some stuff you're just to really tech stuff that's being moved around and more more intelligence whatever you call intelligence is put into these things that's a big big big buzzwords you can fall it another way computer chips became cheaper so it was economically viable to put them into shoes all drinks or whatever which part of the Internet of Things should we focus on in this fall in the media there is often something about the household appliances because everybody wants to get on his password so your fridge will all the milk for you I don't think so Amazon had those batch problems where you can order a specific product to modern described prize from Amazon to have delivered and even washing machines companies will tell you that the washing machine will be updatable with new washing programs just to be that was serious they're turning left and turning right in different speeds how much can you really update on how much is anyway 1 of those connectives applications push us into a very very very important discussion who owns the data if you shall have access to the data so if they see as always cleaning wide mean global those with a high temperature and he always has a special bottom to clean out of a lot maybe they start to get suspicious is suggestive leader from his nose Orosius 0 the killer so even there with a household appliances this discussion I want to unwarranted this discussion of the social impact for this talk we have a very interesting talk this morning about the at is the off my team and there's an open space now so here is an important topic but the focus here the other term in the the title is industry 4 . 0 the very interesting thing that's a Chairman thing and the German government thing the German then set up a work group and they called it Industrie 4 . 0 of course a talk on industry people and no will because it's the chairman of government and the truck chairman but anyway there are multiple aspects of industry 4 . 0 no I 1 thing is there are more sensor data to be collected they hold that the machines will communicate with each other and there is a very fascinating sentence in the final report of the work group Hooman humans and machines communicate and cooperate so if you have ever shouted at your printer you shouldn't be so why don't you print your way ahead anyway do we really need release numbers on our industry revolutions so do we need to release numbers on revolutions and I found a very
interesting graphic and that explains kind of tries to explain what for about 0 in the industry was the 1st thing we switched from Alsace pulling things to water balance the mainly in Great Britain and then 2nd the mass production mainly started with a bunch of us in the United States then copied from the automotive industry the 3rd thing computers and automation and the full of the siren physical systems and I think so that's 1 part we can focus on and that some stuff that some of our customers are really talking to us and all those products machines produce a lot a lot a lot of data and usually they write it to something that is essentially evaluates to death now so maybe it's written to some memory chip on the machine some logging file which gets deleted but more often than not all the data is put into Wayne and that use anymore 4 . 0 the idea and the part of industry 4 . 0 I want to focus on this talk is those in the connection of systems what to do with
it so finding the focus for this talk because Internet of Things and Industry 4 . 0 is a big big big topic with a lot of people making a lot of money to talk talking lot about it we know there will be more sensors more computing divisors in more objects they will produce more the watching and analyzing log files would be a good thing to do I think that's so statement that most current to subscribe to it would be good if we looked at the warnings and all marked files and take don't take actions and finding new staff is something that would really be helpful in a professional field there ethical problems of Mifune you have your own stuff and everybody was contracted but just in a professional environment just think if every worker just spends 5 minutes searching for something and resource talking about personal office of my tools we are not even starting from production materials flying to company how much productivity is lost and it's not lost to fund activities like ping minesweeper it's lost to say activities like searching for stuff 1
plot of the whole sensor at the
town and stuff we're not really talking about with our customers a which they want to implement we're talking about the maintains suspect of stuff if you want to have an air conditioner that runs with a very high margin that it will really be keep on running all have for heating system that keeps on running you have to regular maintenance and that regular maintains a set on specific time intervals and then you have to change specific parts much earlier than needed and sometimes if you have a set interval it will be too late and the machine will break down so the regular intervals the additional costs to because you have to do that in the changing and maybe you do it too soon or too late because you have fixed in the walls there is another way the fixed and broken maintains mother just wait until you conditional breaks down and then you start fixing it the good thing is the only change of heart's whenever you broken you don't change them too soon the thing is often dropped of service not that's the part of the whole sensor data and industry 4 . 0 and of things I really get it's really nice if you grab the sensor data from your machines that are really working air conditioning heating machines in the production floor or the shop floor and you analyze the data and see what happens all stuff happens and can have a dynamic meant to save a lot of money and you can keep the stuff running now why should you share those logging data we had that and consolidated in a big database or somewhere else you could always do it locally but and we all know those jokes about the check engine light you can fix it by upholstered putting on a jet engine life I know it from developing software for end users all the warnings and I really saw how the training in the 2nd or 3rd generation for myself was all this morning always comes just press OK so the local handling of error messages of warnings of check engine lights needs a lot to be desired and those local check engine light those local things giving information they relay on a specific set of parameters that are frozen when the system was developed when it's distributed what is rolled out maybe in in newer generations fathers machine we have new consumables new filter materials that are more thorough or they take notice of the air in the air conditioner thing or they have a long time and you're out given set of parameters is very static if you can communicated to central society can do it and you can also add new analyzes so our focus I have been moving backwards our focus moderator has to be stored somewhere more data has be analyzed now why should you store the data in PostgreSQL something about PostgreSQL
buskers good is an open-source
object-relational databases some very important it's not just in relational database system if an object relational database system so there are some of the Justin and chess tables it's more than 15 years of active development we are strongly confirming through the Office of standard of ANSI SQL you never hit 100 % of a than that but we're very hard trying to be very close on it it runs on all major operating systems currently we are facing out always 2 and some very exotic age the UNIX version for possible pollutant and I put something very in bold letters PostgreSQL was built to be extended that is getting new components a prosperous was planned in the design of stressed well some specific
issues a very good the maximum data by size you can't put all your introductory treats Interpol stressed out it's animated among Mexican run of roles but is also unlimited truly we have a maximum table size of of 32 terabytes and increased size of 1 giga gigabyte and that's sizes that really are tested and which are supported and which work in practice a very very important parts and the speaker before me was talking about the license is the pulse crystallizes if if kind of MIT license that's the legalese I've shortened it do what you want with a softer if it breaks don't come crying crying so you can do what you want with the software you can bottle it you can resell it and this gives us some very nice aspects the 1st thing Our within open source software there is not every open source offers equal some open source offer is owned by a company the and companies are sometimes very good for the society we think of k . com what they did an awesome party last nite and sometimes they have do no evil for some time in the slogan but sometimes they become evil or sometimes they Wendish so and company owner myself so it's no capitalism critics I just know that that computer companies are not here for ever and their current policy is not here forever so it's very important PostgreSQL is owned by the PostgreSQL global development group it's like Titan which is owned by the pardon softer foundation just more safe because apostrophe flow be development group is not really a legal entity you could you or get from the planet the open development of pulse crisco is very very open we have an open discussion about new architecture new features new comets it's open on the mailing list the discussions that lead to go 1 way or the other I always researchable if we're talking about complex technology also things the database is not doing is very important for the development history what led to do it this way all this out in the open all the things that we have a beaker silence of against being bought by some company which happened with other open-source projects we have 2nd quadrant are 1 of the biggest contributors to the current pulse stress go cold we have not been there for all time so all 15 years but currently we still contribute less than 50 % of new coach growing things of 30 to 40 and we have the the crew before of 22 commit us on all stuff but even if somebody would buy us a 2nd courtroom and as 1 of the become tributer suppose stress girl it wouldn't really matter to the project there are still a lot of more contributors and if they buy us our people would not have to stay within the company they could go out and work available somewhere else that's gives a very very strong results the pulse crystal brooch at and that gives the trust which also that the trust in me to put my money into PostgreSQL the lies of PostgreSQL is open from errors this is models which is very important because you can't survive by selling stuffed animal with a low born at it's not possible you need to try different business models we 2nd water and have the degree of business model of selling support and development and early access other companies like all main coveted Enterprise DB they sell of proper Tyree fault of all stress with some additional features green Blum transcytosed on the B did the same thing they made their own version we know of many other contributors to suppose stress good health kind of an Einstein model off their employment there government employees in the NRO somewhere in the United States and in that time as DBA they also do development for PostgreSQL and we have a very specific culture of PostgreSQL development there are always some big companies like ETV 2nd quadrant front relative a cyber tag crunchy Data solutions and some or all of the world we compete for the same customers while contributing to the same code base so it's a very interesting and not conflict-free environment but it's also very port moving now why
store all those data in the database and wine a relational database the idea is if you get sensor data lot fliers posters and tracking from your stuff and put it into a database you have a common ground to put your analyzes on it that analyzes can be machine learning or programming to analyze the data it also can be data scientists and that's the big benefit if it's a really relational databases because there are many many tools for non programmers to do a data analytics on relational data so possible impostors knows intermediary for you all the data off union of thing in history threefold 1 0 it gives the possibility of people from other fields outside of computer science and programming to come in and analyze the data with their tools and with their mother why
should you store document they'd have like the sensor data locked files and stuff into prosperous grow you could use a document database all stress Girl 73 Russians as a adjacent the datatype to store documents in it and Posterous goes still has a broom Crary language SQL Structured Crary language pruned by many decades of experience designed for non-computer scientists to write queries Jason the data that may be corroborated by SQL 2 is the data has a full index support so searching for tributes within your chasing the objects can be index supported and the PostgreSQL optimizer knows how and when to use which index to just get the right roles you don't have to program it yourself we can later I call it the Hannah Montana my users and have the best of both worlds like putting out regularly covariates attributes from adjacent the object in 2
columns and what is seldom known up a when you just read the actual blocks of all stress features those chasing the data types are founded on multiple generations of code so it's not the brand-new fresh coat of course fresh but it was used and use and use before it started out in
2003 by terrorists again all with that H star data type which was made to start something that's like arrays it was a great if you were 1 of the highly trained to brushing astrophysicist 2 very efficiently store all the data the challenge was if you were not a
highly trained Russian as surfaces it was very challenging to step to deal with H star so it took off in specialized communities like the astrophysics like the ideological Data community but for the whole thing it was not really grasp of what to do with H star and how to put data in now on the foundation of the H stop all the experience of indexing non relational data that's stored in these fields on that experience Jason the and Chazan datatypes were integrating the Posterous go they share a big common code base within PostgreSQL long experience with indexing the stuff very good indexes for this stuff optimization of this stuff and the chasing the data table chasing that runs the about note how to the the I mean that of the book database is very short you have a title case-insensitive text you have a I is the N which has almost been digitized and
you can do an index on books with the pump in fulfilled and the publishing into a fulfilled can be a chastened object with any number of attributes and just by doing this index the you can search on any at tribute of all the chains and the objects index supported you can search
for them anyway without writing of your own program just by covering it but by setting up an index it's index supported index supported just a short explanation but if you read through all the lines in the database you have to pull a lot of data which takes on a file if you have an index it's a shortcut it's like Irvine searching for word in the book all the time are just going from the index in the front of the book so that's the kind of car you can do on trees the data I have just 1 example that parallel normalization I says that I told you about are when I'm developing database applications currently I always have this from a from would that we follow but it's for special use that as I always have 1 column in my tables for the specifications my customers did not tell me when they ask for creating a new table and this table is created as Jason being so every I have reviewed that belongs into that table that was not discussed when the specifications are written up just put into that Jason B. thing so I have for a user table without having the Twitter handle in I put the Twitter handle into the Jason the field and it stored if there's a next cool thing like I flip shared or to chat with service to adopt but for chatting and with blocks or whatever I can put the new handle into that that the now if that thing really takes off you want to move it into the relational field you can that's a column for that
uh tribute from your Chazan being and you can transform all you stored data and you don't have to adjust your applications you can write a trigger which every time the always updated looks into the chase and B field and writes the stuff into the regular columns so you have the Hannah Montana
my literacy of the best of both worlds you know the chasen B which still can be used and you have the column data which can be used in euros exudes or reporting stuff and if you have migrated all your application to use a column you can drop the chase and be of abuse storage forward why columns and why good 1 of just need for of primary and examples chosen be why do all this stands to get the best of both worlds we have documentation which is given by the column names we have additional optimizations that are even stronger than gene index we can have on trees and b and evolve analytic tools which really deal well with column will temporal data not another part which makes prosperous vote really really a good choice for all those new data types from new sensors is exact stems ability extending pulse prescribed by new data types which can be used from all application which can be in support of is something that can be done in the pH not being the don't a pH using it a master thesis something around that's the efforts to period and a lot of people do it I have 1 example light of they top 1 of the big things with all those so self-driving cars coming up and currently is used for a geographical things the planes fly over the city and the lightest can you have lots and lots and lots and lots of data types data points and to store them takes especially because specific form because if you would just take every coordinate into an integer into 1 column on the overhead with those millions and millions and millions of points which are stuff make it feasible to search something so 1 guy created a future point cloud data types and he is with the Canadian government for major research and it just extended PostgreSQL by a data type specific for lighter where he has found specific ways of storing optimize light of data become president he makes a specific you searchable and he just takes some features of that led up to 5 which are all specific to it those optimize datatypes that's been impostors go from the beginning it was designed for it and with all those new sensors report and stuff we have not been thinking of last year it was stressed that is prepared to put those extensions and 1 thing my colleague of oral and and the other developers of PostgreSQL within into last Russians if very cool if you have a lot of data that has a kind of normal and natural ordering what's normal natural ordering if you have time based the tire like log files Look things usually those lines in the log files have extending time a scanning time you don't jump within time colonists is slowly growing if you do a light of can all by a plane that plane usually moves in 1 direction so you have a notion of natural order off to the time the bring data types brought range index allows you for every block of data on the hard drive on your system to trust or the beginning and the end of that data instead of having an index to every role in your data you just have the beginning and the end of a data block that's similar if you look at those old libraries or in the all companies when you have the physical storage of customer things from a to B from C to E from F. to whatever and we started in the brain index what's good about it it's a very very small index for a lot of data the bad thing is from the index don't get directly to the role but if you have something like temporal data which is strictly ordered by time or you have something geographical data which gets from playing scanned and you spring then index you have a very small index very small index leads to a lot of index in your cash maybe in your main memory and maybe even in your level 3 or level 2 cache of your process so it can be used very quickly and you get to ride out a very fast 1 thing that will be in
prosperous grow 10 which is scheduled to come out in autumn this year decorative
petitioning what is petitioning and why should we care if you store your data in a table it will be a coming in and appended to the end through trust for the about the spend only to the end and the and the Indian now if you have flocked
files of robots in the factory you are not really interested what this robot was doing 2 years ago that's why sky came to power nobody look what it did 2 years ago but in a practical environment you don't look at the data that happened 2 years ago you need just the last 6 months or 4 months or 3 months because layout earlier data is no more relevant for today's actions so what he did in an efficient way to delete the data are that property was produced more than 6 months ago more than 7 months role more than 8 months ago if you have everything in 1 big file so January February March April and all in May he decides to delete generate you have a hole in Europe file database follow which will be filled up and if the data from May which will be put into those free space is longer than generated and you have some year and from here which makes it hard to search also and deleting data from a database takes a lot of y all because we have to declare every record as inlet that's the way possible works if you have a petition for every month you just tell the system drop all the data from January yeah a petition for generating and because it can just drop that petition I've put it out here with the data for February and data for March and the decorative petitioning in earlier versions from PostgreSQL you had to work very hard to do this partitioning you had to write regard rule colds to move the roles in right petition under this now with 10 . 0 and that's 1 thing Robert Haas and the other guys from me to be really push for what you have this decorative petitioning which allows on a decorative way to say yeah output the start us there and then have to dropping looking really forward to this feature the another stuff I mean we have a lot of features impulse stress grow there are additional these special features I told you about that point P G . out before I also mentioned briefly not really really know what was on the slide postures withstood geographical data we have a lot of more extensions of the running and if you have extensions that something like packages and we all love a specific programming language which currently I think we have 5 to 7 packaging systems and piping which is great to have a lot for t which is challenging the US has to deal with which 1 stress girl it was worse we didn't even have any structure to have those extensions so people distributed makefiles and an instruction how to install it which kind of worked but was really scalable modeled 1 of my former colleague Dimitri was the the developer of those extensions we have a crate extension extension name and all the extension updated so the whole life cycle a cycle of extend the functionality for PostgreSQL databases can be managed with commands great extension up that extension modify extension we here so we have a nice way of packaging and distributing those information
no another thing I to look forward in those in the thing and industry 4 . 0 application you might want to communicate with the devices somewhere in the world and you have a master database where all your company data is and being the Internet exposed database you just want to have the data that it's really really necessary to communicate with 1 specific device because every data that's not in that database cannot be compromised or stolen soul evokes all 1 with uh 906 9 . 5 somehow and we invented logical decoding impulse grows logical decoding give all the changes that happens to be database in a logical kind of human readable format but also in a machine readable format so every change that happens to any table in your database is written by PostgreSQL in the binary lock anyway and with logical decoding we found a way to extract information from that binary lock and use it for different purposes so with the logical that's an open-source extension disappeared but 2nd quadrant based on that teach a lot on that lot of coding with impostors girl you can do the following you have
2 tables that are relevant for all you off to DB to supporting database for Microsoft and you just want to replicate those 2 tables to the outside use of the
geological to get that streaming data outside transcoder write-ahead log in readable form and that's essentially a thing is set up the note the master database you create a replication factor which tables should be replicated you add the tables you want to be
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Metadaten

Formale Metadaten

Titel PostgreSQL - The Database for Industry 4.0 and IOT
Serientitel EuroPython 2017
Autor Massa, Harald Armin
Lizenz CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
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DOI 10.5446/33719
Herausgeber EuroPython
Erscheinungsjahr 2017
Sprache Englisch

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract PostgreSQL - The Database for Industry 4.0 and IOT [EuroPython 2017 - Talk - 2017-07-12 - PyCharm Room] [Rimini, Italy] Industry 4.0 - the current trend to make more use of data technology and analysis in manufactring. IOT - The Internet of Things, where many ""things"" currently just loosing their information will transfer and store them within central systems. There are aspects of those trends most do agree on: There will be orders of magnitude more data to store and analyze. More agents will need to connect and interact with databases. This talk will explore what makes PostgreSQL an excellent candidate to be the database for managing all that data. Strengths in development, culture and community, extensibility and robustnest will be presented. Selected features of current Version 9.6 and the soon-to-be-released PostgreSQL Version 10 will be discussed for their value in those trends. There will be an explanation of their technical realisation, and special pointers how to use those features from PostgreSQL

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