[Music] welcome to this afternoon’s session migrating to cloud spanner my title is Sammy xuer Dean i’m a discontinue solution architect with Google cloud joined in these days by using Neal from across the pond we’re both gonna spend the next 45 50 minutes with you going over all types of eventualities on migrating from digital tape archives to cloud spanner just kidding we’re no longer going to talk about digital tape archives intent spanner optimistically that is one other speak if you need that talk speak to me afterwards so absolutely are coming from much more trendy frameworks much more intriguing database picks and quite what we want to do in these days is talk about that i am going to speak about cloud spanner if you hear confidently that’s considering anything externally enticed you to want to look at the place the migration would look like but we’ll go over actual quick what the historical past is on cloud spanner and why you may wish to recollect it we are going to speak about mostly how we’ve got thought about migrations and how Neil and i have put together variety of a sequence of steps that we believe applies to most organizations in the way that they will process a migration but we relatively want to make it useful for you we now have chosen a pair case reviews that we are going to walk by way of step by step and show how you could possibly go from a supply approach into cloud spanner so optimistically you will leave right here with something tangible after which finally we’ll wrap up with some closing ideas confidently that sounds fair so rapid background on cloud spanner its internally used within Google as spanner it’s our transactional report of State for hundreds of thousands of functions and it was once born not form of in the opening and the establishing Google was busy fixing interact the it index the internet and style of find all these large patterns and provide significant search and it wasn’t anything that was firstly tackled until it became critical that we did deal with it established on the size of some of our businesses however what we did realized a lot of challenges that we had been overcoming are confronted by means of various businesses how do you at scale preserve a database with excessive reliability high durability transactional throughput anything that can be used in fiscal transaction and so cloud spanner is the externalization of that we comprehend a lot of buyers have the identical challenges and have long past down special paths to try to clear up it so in case you are coming from that kind of whats up vast vast use of information however I’ve needed to make trade-offs up to now needed to pick what you were willing to stop confidently this talk will probably be applicable to you it’s corporation-grade google uses it to run a multi-billion dollar manufacturer we have different customers using it as well but fairly it’s designed with a high SLA in mind to be strictly consistent it is acid compliant and it is disbursed it is the thing that quite a lot of corporations attempt to project try to resolve with disbursed architectures with a multi server method with multi nodes with a variety of interconnect and plenty of district allotted storage it’s all that but rather it can be just a database at the back of an API it gives you all that dispensed nature but you don’t particularly have to do a lot to get by means of to it it can be relational in nature so relational information is type of just like the easiest thing to get your head around if you happen to’ve been around databases it’s been round for an extraordinarily long time it is something anyone’s can form of reason about when they go from one team to our one other within Google we worth developer time substantially and it does not make a variety of experience to have developers transfer from one workforce to one more and variety of have to say well what stores are making use of how we’re utilising it what are their canonical queries every body variety of gets sequel and gets a relational mannequin lovely well and so there’s a little or no low friction point to maneuver salient lis between groups and say oh yeah i do know you are making use of spanner at the again finish i will get going on that and it can be horizontally scalable it is now not so much it’s no longer this form of heavy-passed that you can scale up however you are not able to cut back and it is now not the place you need to make a ability request history you kind of poke an API and also you get much more transactional throughput by means of to it just spin it up it’s pretty simple you identify the example choose a region pick a quantity of nodes and hit create I simply wanted to show that cuz up that used to be lovely cool animation all proper I didn’t make it so quite you just ought to rationale about two matters and then i’ll turn it over to in naming and pc science is the whole lot correct so identify you have to name it however then you definately need to decide upon how many nodes nodes is particularly simply your unit of potential it is the most touchy thing to fee you opt for what number of nodes you want and we’ll go by means of variety of what every node gives you in somewhat bit after which the place do you need it so how a lot capacity do you need and where do you want it which area do you want multi region the product comes in plenty of distinctive varieties and the final thing is take your code merge it along side our patron libraries or speak sequel to us after which you’re competent to head we understand DDL as a database so things that are used to doing in different databases are lovely handy to make use of equivalent like bigquery and other merchandise there’s a built-in question window so that is the fundamental it particularly takes what I describe takes longer than it after which it in reality does to virtually get began with cloud spanner so now let’s speak about migrations how we’re going to speak about the rest of it the applications are going to walk through in terms of the migration realistic examples Neil’s going to talk through that so hi my identify is not any Mark Richt i’m an answer architect from Belgium and so on this part i’m going to give a common framework for migrations supplying you with a excessive-stage plan of action for migrating your software from the present database to cloud spanner so step one you have to isolate your whole database entry code in case you obtained it distribute in quite a lot of modules for your application together with in any any lines of code it’s best to isolate that all right into a separate module and that will be the one location where you have your entire database entry code and be certain your progress group best adds new code in that module so you understand exactly what code talks the database and precisely what code desires to be converted throughout the migration process by and large it is a superb practice considering the fact that it gives you one single module to experiment your database interactions and similarly it allows your unit trying out of your application we only need one single modeled module to mock out you don’t have to have–you a experiment database you don’t have to have some weird and unique means of constructing some some knowledge that takes care of some bizarre distinct edge conditions that you may mock all that out and give this unhealthy data to the rest of your software to test how your utility handles it it makes it a lot easier to find and analyze any elaborate sequel queries you’ve got acquired to your application and it offers you a single point so as to add metrics and alerts for monitoring your database access for example you would add an alert for query latency in order that you recognize when your crews opening to get somewhat sluggish it is time to resize your database add extra power or you need you see which question distinctive queries are gradual so you do not need to dive deeper find out why they’re gradual probably optimize a question a bit higher trade the best way matters are read probably also allows you with metrics to assess the frequency of reads to the tables which can offer you an indication of whether that you may add some consumer-side caching to your database layer accordingly giving a performance enhance to your applications it now not wishes to read from the database and get it from the nearby cache and of direction failure signals so any read/write disasters any any inconsistency problems you have got received a location to alert it and catch the pond earlier than they before the begins getting quite dangerous and as I stated you will have got a single remoted module for migration so your next step is to add the code to that module that reads and writes to spanner sounds easy but we are going to appear into extra small print about that later you’ll be studying and writing while as studying and writing from the long-established database you would comprise capabilities in your software that are not to be had in spanner again extra on that later and code could be reading to and writing from each at the same time but you would have one database as your source of actuality at the starting of path if the usual database and as soon as you may have entirely migrated to your knowledge over and you’re sure there is no inconsistencies that you could switch to cloud spanner as your source of fact so rights when you are correct right into a database take row you must simply ban that you just will have to update the whole row you shouldn’t just update the columns and that approach you are making sure that the data are writing to spanner is utterly up-to-the-minute on reads that you could read from each databases and compare any inconsistencies and report those inconsistencies once more that is to achieve self belief that your migration is happen appropriately and once your information is imported and the whole lot synchronized there will have to be no inconsistencies and no extra failures one more thing you will have to be doing if you do deletions of rows to your database you should keep a log of these when you’re importing information and data my rows would have already been deleted so you do not have got to be we developing these rows you’ve already deleted whilst you are doing all your import maintaining a log of the deletions will allow you to investigate whether or not this row has been deleted when you’re reinforcing it and eventually one relatively useful factor is commit timestamps some databases do that mechanically spanner it can be an option you might have a column which is the instances time when that row is being committed and you should use this to know which is the latest date information variant whether it can be the information you’re importing or it’s the info that’s already been written by using your utility to spanner and also this module one more thing allows you to canary the use of your new database you turn the sources truth in part which you can megastar some application circumstances speaking to spanner and a few tokens long-established database so in case you you trap any problems early that you may roll back so how would you sincerely migrate good simple process you change your database schema to cloud spanner schema and create your database you close down your software you do your export and import while your database isn’t being written to so it can be utterly steady and also you start it up once more this is not an best direction for several reasons to begin with there isn’t a rollback your software if you happen to start noticing after a few days matters are going wrong some information’s getting corrupted what do you do you can not roll back given that you could have obtained a couple of days new information you can not fix the information you can not you just like to panicking in case you roll back you may have misplaced the info and your difficulty and secondly your utility is down if you’re moving to spanner it’s possibly in view that you want to take skills of the scalability and the availability so you wouldn’t want the downtime related to an export and an import of a enormous information set so what we do we wish a are living migration approach as soon as once more you begin with the identical means you create usual create your database on cloud spanner and you export an import from your normal database to spanner but this time you hold the applying stay strolling now of direction whilst your application is walking your exported data is already obsolete that’s not a main issue seeing that we are going to see you write to both you keep the normal database as your source of truth and proceed updating rows and spanner there will nonetheless be some occasions inconsistencies however that’s why your usual database remains to be as Sasa truth then while that is going on you do one other import and export of any changes that have happened considering the fact that the final export now this will carry your data in sync offered that you simply simplest write rows that haven’t already been updated so you also this factor replay any deletions which have occurred and when this is completed we or it should be that your cloud spanner database is totally in sync along with your original database and the monitoring you’ve gotten added on your database entry layer is probably not showing any further inconsistencies will not be displaying any further errors that you could repeat this last step as usually as you want and at this stage which you can additionally run a massive evaluate to see which if the whole lot is in sync subsequently when you’re satisfied everything is good not subsequently sorry you switched to B this cloud spanner as a supply of fact once more like I acknowledged earlier than you can do this as a canarian process that you could in part switch some utility instances or a percentage of the traffic and then screen things see if matters just right and step by step expand the chances that has being written to cloud spanner and if matters go improper that you may right away rollback on the grounds that your usual database continues to be being written you have got received a perfect rollback role to head to you do not lose any information the whole thing’s first-rate but in the event you’ve obtained if the whole thing has gone ahead the whole thing is working well and the whole thing’s constant then which you can turn off the code the rights to normal database flip off your additional database shut it down and you’re fully walking on the spanner and at this point of direction you will have your launch occasion and you are again to splats I mean now who will speak about the example from migrating from a no sequel database to a cloud spanner I particularly wanted to have the celebration yeah later later adequate adequate migrating from no sequel so the apparent factor here is that spanners known as a sequel database but we have now quite a few shoppers and a variety of curiosity for patrons coming to us and pronouncing whats up I made these design picks in my utility stack a while in the past where i could not scale in a relational database a traditional relational database very conveniently and so I needed to make a decision what I was going to stop and most the time businesses selected to quit transactional consistency hiya let’s give up transactional consistency because then we will shard quite without difficulty or they decided you recognize it’ll hold a relational database however will employ some kind of shim some type of sharding shim and so we’re now not really getting real transactions throughout the entire database in a single context but we will need to variety of manipulate it and introduce some plumbing in between so relatively the point of this slide is that you may have your cake and devour it too spanner takes care of that it takes care of that ongoing proper horizontal scalability at the same time giving you transactional consistency whilst giving you the capacity to remain high in phrases of to maintain an extraordinarily high uptime after which it will get you again to an extraordinarily simplistic model the place you’re now not having to maintain is that this key worth is your file is it you already know what’s the underlying storage this is quite simple to realize sequel semantics so when does it apply so when would you do that you wouldn’t do this for some thing that is highly volatile in nature so if you’re simply preserving track of the important thing and then you could have an arbitrary quantity of attributes related to that and it’s relatively difficult so that you can get a take hold of of is there a steady is there a well-known consistent pattern to the attributes we’re maintaining monitor of with the suggestion that those attributes would translate to columns then this wouldn’t be a pattern so that you can follow right this may be fairly if you are like you recognize mainly we’re making use of it so as to preserve track of unique attributes the collection or the set of those attributes is somewhat static might be some attributes add here there but that is k we are able to do schema changes within spanner but it’s not too it is now not too different it is now not too all over the situation moderately excessive quantity spanner is a jogging service which means you instantiate a designated quantity of ability to it so if you’re most effective transacting with the database at a trickle quantity it’s some sort of light search for or whatever that is no longer it though we use cases we’re seeing our individuals which are saying you recognize i’m wholesale jogging vastly excessive transactional throughput past beyond just a gentle workload the source database should have a gorgeous easy means I believe most information in these days we will have a lovely handy option to import and export information so you understand very similar to what Neal was bringing up not but much much like what Neal was bringing up in within the import-export or imply the migration normal framework and the last thing is it can be an actual plus if the source procedure has some kind of mechanism to do the equivalent of change information seize if that you would be able to variety of be aware of what’s coming in out of that database it is fine some supply examples that we we’re seeing a lot of our individuals that are strolling their possess Mongo infrastructure possess Cassandra infrastructure that also type of wish to get out of that sample but also individuals coming from more common or extra provider important carrier choices like DynamoDB so we’re gonna decide upon this kind of to stroll via migration any individual want to take a bet correct so dynamodb very well so it is pretty easy it can be a it can be virtually not that difficult DynamoDB is a single table constitution it’s now not it is not many tables related to one it has some first-class fascinating similarities when it comes to cloud spanner in terms of the best way keys are laid out but but it is a table and we will go by means of an easy route this style of aligns very effectively to what Neal was once speakme about the place we’re gonna have a bulk loading route that is going to return in by way of unique export points and then we will have our trickle feeding or streaming direction will collate those on to the blue icons or cloud Google Cloud little basically coalesce these onto the cloud part deliver those collectively utilising a technological know-how on our part to name a product known as cloud dataflow and then they’ll make their means into Spanish so let’s construct this together homework before you get began is is to estimate how much cloud spanner ability we will use normally there are some principles of thumbs regards to how much storage must be allotted per any number of nodes so for those who feel you’ll be strained on the storage side of matters you could need to scale up the number of nodes and so it is truly a quota procedure of two terabytes per node two terabytes per node and so if you’re gonna exceed that you simply simply need to form of overshoot that to okay sufficient nodes to cover that if you are good within that then you’re going to design on the part of throughput and spanner which is how much transactional throughput do i need which is the 2d point is so now i understand how much storage i have how a lot IO do i have on this database after which realise the information model the place am i coming from so in the case of in the case of a DynamoDB origination dinamo has a couple choices for how it buildings its most important secret is it hash or is it hash plus variety like we mentioned within the last slide then throughout all my gadgets in my desk what are what’s the superset are the set of collection of attributes so that i will be able to fully grasp tips on how to create my columns what are the info forms of these attributes after which also hold monitor of any secondary indexes this kind of in case you do this as a worksheet or as like I stated as homework it units you up for a first-class migration direction first step is understand the variations the data varieties are quite often there however there would be some variations to recognize how data forms from one map to the other on the whole you’re going to seek out all of the identical knowledge types if now not more however understood that is the canonical mapping of knowledge forms so let’s take a let’s make it functional let’s start with a baseline DynamoDB desk this can be a desk you would create it’s making use of a simplistic hash key as its as its principal key it’s now not utilising hash and range and it can be a hash key referred to as consumer name we now have a little bit of provision throughput and what i am not displaying on here is that as a way to facilitate that streaming hook this table would even have streams enabled dynami to be streams which might just be a further flag on the top of this otherwise you might adjust your table if it’s already you may have a desk that’s already jogging you might without difficulty argumented and add streams to it so let’s create the identical table i’m kind of taking that metadata I we went via in the homework assortment and we will create the an identical table and cloud spanner and so shall we embrace that we’ve got determined in that supply table now we have looked at all of the attributes inside our DynamoDB desk and determined that fairly there is just kind of four regular attributes our 4 attributes that symbolize the vast majority of what we’re what we’re watching at it’s like zips code subscribed you know whether a person subscribe to a ft or not when they are there send sent a reminder date possibly some aspects they were and so this fictitious desk nevertheless it’s mostly not too diverse from the best way that you would use a easy database or an easy database like DynamoDB that is extra sort of key worth oriented so will would that properly on to a cloud scanner schema to get to that factor kind of in the commencing I alluded it can be actually particularly trivial this is just about everything of what you need to get going inside cloud spanner is decide upon where you need it how so much potential you want and what you want to name it in the event you hit create and that i suppose we’ll be showing this later in the event you create it is a number of seconds a number of seconds you could have bought that so much capability sitting there and Sona and a 3-node regional established this is roughly 30,000 reads a 2d constant a 6,000 writes a 2nd what’s a lot of potential above all when you are speakme about might be dealing with a lot scale down potential in terms of provision throughput just for three nodes you get lots and three nodes would be form of the minimal for a production measurement setup there may be additionally multi-regional which suggests more quorum copies and inspire you to move to form of a cloud spanner one zero one speak to recognize type of how this the quorum works and the place the rights are dispensed however clearly for those who do that inside a number of seconds you have got obtained a huge bucket of enter output in order that table I confirmed on the prior screen that stated howdy we’ve got analyzed our supply table discovered the way it looks in dynamo discovered the columns how can we map the columns to anything database oriented so within the illustration so the previous screen I showed methods to create an example inside that illustration we are able to now begin instantiating databases databases are variety of logical containers the example is ubiquitous see of capability and then the databases are particular logical units inside of that database that you can create tables appears and feels mainly like another database it’s really not that diverse however we take our DDL which is usual DDL plug that in and create our database one factor that we do at this factor in our desk is we run back to our dynamo table and using dynamodb streams and lambda we want to capture all the changes off and so i would turn around i’d make a operate like this a lambda perform like this and this becomes the glue between all of the alterations happening inside of my dynamo be desk and all and getting it over to the Google cloud side and we’re utilising clearly pub/sub within the core so truly what i am announcing is inside of my lambda perform every time I get a transformation I’ve obtained my dynamodb streams to configure to ship me the new photo dinah perhaps which you can say send me the historical picture the new image or each and so all i am doing is i am taking the whole payload i’m just shoving it over and this essentially has lambda make a call and sends it over to pub/sub will exhibit there may be an motion in a minute so it is in pub sub pub sub is our tremendously scalable allotted messaging method where case you already know you could be pumping messages in you know a million a second or some thing ridiculous something your software wishes and have n number of subscribers they can be pull subscribers or push subscribers or some thing is contacting and polling for messages or it may push to an endpoint any form of endpoint like a cloud function or whatnot we’re gonna be utilizing a pull mechanism this might be an interesting time if your application had the luxury where you can also this may be the inflection point at which way you can also make a decision like whats up for consistency’s sake let’s do a quick pause at the same time we kick off and export it’s now not strictly wanted relying on how a lot information you consider is gonna be mutated throughout this time or overlap of keys but this is able to be that second you could possibly decide good day you know we’re gonna kick off an export must we pause rights for a second while so that we are able to hold track of precisely when this lambda operate it was instantiated and when the export used to be kicked off it is a momentary factor that you would ought to come to a decision it is no longer strictly wanted so how do we get information so we’ve got already put in the lambda operate that’s sending over the streaming data truly now how can we do the bulk in order that becomes our checkpointing time like put on this operate we started collecting knowledge that is changing as of this moment now how can we do the mass export so you ought to lean into the platform that has that that host that information supply in the case of DynamoDB there is a tool which you could run a data pipeline job that is the canonical technique to get information out for those who have been to go and say export however what it does is it lands that knowledge into an s3 bucket it kicks off an EMR procedure lost of MapReduce method reaches within the desk and then kicks out flat documents that our JSON files and puts those into an s3 bucket so if you feel again to the lambda perform that lambda perform used to be our glue that received us from changes happening in dynamo over two pub/sub when you suppose about our s3 bucket the glue that might have moves it from Amazon facet to the Google side is as a copy command earlier than you do the copy you simply sort of seem on the bucket there must be a hit file within the export on the way to let you know that the whole lot went proper but nearly you should utilize the GS util it’s a Google storage utility that is familiar with the way to read Amazon credential documents so this can be a very useful feature that very nearly shall we say you’re working on an illustration or you are working inside of a cloud shell and you’ve got hooked up the Amazon command line utilities and certainly now the Google command line utilities together with GS util GS util is aware of learn your cameras on credentials in the event you you already know if they are configured on the same field and which you can literally cross it in s3 URL so on this case i will say go from the s3 bucket to my Cloud Storage bucket and an R sync so just inform me the whole lot that’s there particularly giant switch we’ve got a background operation known as cloud storage switch service in an effort to do this for you within the historical past and then on now each sets of artifacts both the pubsub streaming changes as good because the flat records from s3 or sitting or have have shown up on the Google aspect of the fence so what do we do with these things the very first thing is we do a a job to import all these flat records from s3 so we’re gonna we might kick off a dataflow job and knowledge flows are managed provider for managing Apache beam pipelines so we’d have a pipeline written an Apache beam pipeline that is aware of easy methods to take flat records and JSON format and write those into cloud spanner utilizing anything known as spanner IO which is a mechanism for Apache beam to put in writing to spanner and that will run via and that will complete and that is the satisfactory factor about cloud dataflow is it takes your Apache beam pipeline after which offers you this very type of introspective view into your pipeline how it’s and how much you know the way many messages are being written what was the success element and so you can display the development verify object counts when it’s finished perhaps do some selects between the two data is and make certain that the item count between one desk and another table are the equal and do some spot checking style of appear at an object and one appear at the item in in a single database and look at the item one other one you’re going to need to do this may be four exceptional objects inside of your inside your database so now the more exciting assignment which is how do you get those streaming changes which have been coming into the pub sub-q which haven’t been picked up yet how will we get those out and pushed into spanner so now we want to create a subscription to that need to create a subscription to that topic and run the equal thing however this is now a streaming job this will not terminate like the other job which was once a batch job this is a streaming job that kicks off and it is very an identical this can be a dag structure which is like practically a structure of activities that you’ve requested to happen in a chain and now the streaming pipeline will stay in in continuum it can be now not going to terminate considering that you assume messages to hold coming in unless the migration is completed proper and note this does it is rather unique it’s it’s now not simply new documents it is it has to look and spot is that this a kradin are an update and or a delete this is since the spanner API calls that do these are slightly special and so you must separate this logic so I’ve proven you some dataflow code i do not need to make this slide a texture so let’s exhibit you some probably the most history at the back of it so let’s look on the batch pipeline it is just a little extra concise for cause of demonstration however this is Apache Beam code it is a type of a trim down variant of the pipeline you create these pipelines and also you nearly simply create these levels within your pipeline and it is a pretty straightforward one you could annotate it with variety of a pleasant identify so as to be represented in the UI however I need to learn gadgets I wish to parse items I want to create mutations and write gadgets sounds pretty sounds like sort of the canonical events that you’d go by way of and let’s look at this type of let’s look at like parse objects which is basically how do I take that incoming JSON that’s coming from the files that are coming from dynamo and how do how do I map these what’s that what is that step that just said parse objects in my Apache bean pipeline what that is doing is its mapping it to a Java object in this case and so you could possibly have some code that says hello map JSON which JSON with JSON and bought this object representation of every file that’s coming via so now that I’ve received each file that is coming through the next thing in my pipeline list used to be create new tations create mutations takes each and every of these type individuals now and style of lets me map them into column names so that used to be the 2d this was once the second step in that pipeline and so as soon as that’s achieved then clearly that is that is pipeline has what it desires one thing i will contact on is the Dynamo we mentioned that might happen would have a reasonably unique main key structure which would be hash and range that is the place you possibly can take capabilities of a feature inside spanner cloud spanner called interleaved tables where one desk can also be nested inside a different table by means of attribution of a almost always shared most important key or the first part of a fundamental key so if you notice these boats share say username as a main key but also order number this bodily co-locate s– data that’s like and fro so the for the essential key was neal and then the subsequent thing used to be Neil and his orders those would be form of co-placed from a storage perspective they might be operated on with the aid of the equal nodes within spanner or they would be technically being the identical cut up as a way to be managed with the aid of the equal nodes this makes things like co-placed this makes things like co-located joins very quick and efficient also secondary indexes in the event you consider the customary interrogation used to be are there any secondary indexes any indexes on non primary key fields you possibly can turn around and now at the finish will be the time to use that and spanner does the identical factor when you don’t have a secondary index and also you scan you ran a question on a non most important key field you’re nearly going to get a full desk scan coming back at you so we need to create a secondary index on whatever columns we’re going to be exciting to our question so i’ll do a quick little run-via on verifying replication this is demo time so that is customarily when the sweat beads start so if we could all right to be able to be respectful of time i’ll simply style of run via some trivial i’m gonna create three keys i’m gonna MA i am gonna care for three keys in my dining with table i am gonna have my add key my exchange key and my delete key i am simply gonna so the add one i will add in see if it comes over to house the trade 1 i’ll exchange an attribute in the delete 1 i am gonna eliminate i am gonna clearly see these happen after which stroll by way of everything that happened so let’s just affirm just a few matters quantity one is I don’t have any I shouldn’t have a key I do not have the add key that’s the one i am about so as to add in let’s look on the key i will trade key i’m going to exchange proper now’s currently set to false and so any person wish to take a wager of what i’ll change it to real all proper and then ultimately is i’ll run delete and so there’s a file there that we’re gonna wipe away all proper so let’s go and mess with these things on dynamo facet so i am in my dynamo desk the first thing is i am gonna just add my add key and i am gonna add boolean and bloodless subscribe and i’m gonna call it false so let’s add that and i’m gonna additionally then alter oh i’m gonna change this key should you don’t forget it can be set to real or false is it proper it is gonna change this key and the last thing is i’m gonna alter i am gonna eliminate ok so these are variety of the canonical crud operations right what would happen if I transformed what it could happen if I factor ok so I’ve transformed everything on this aspect so let’s appear at our lambda operate actual speedy so our dynamo table is established to have a set off this trigger is DynamoDB spanner lambda perform that confirmed prior and that is that perform some things i might factor out is that that operate most likely wishes to function with some credentials with a view to talk to the Google API is those credentials do not belong in flat files or any variety of extractable measure you are going to wish to set these as environment variables for your lambda operate and you possibly can take the entire service account JSON and shove that in as has an atmosphere variable in your function shall we say in this case carrier account that is in fact no longer my carrier account JSON k after which let’s check cloud watch and spot if any logs got here by means of so is that concerning the right time that matters came via so this was the add the important thing I introduced that time stamp must be about correct now I brought my key and you will see that that truly new snapshot straying my id my key boolean false and then that is the important thing factor to pay concentration to is pub/sub identification so that is the lambda function having contacted Google pub/sub and the Google pub/sub API announcing here’s your pub/sub id again and essentially my change key one can find that the old photo was or the brand new picture is correct the old image is false and my delete key you will find that it was once a take away and it was once eliminated ok so in cloud dataflow this pipeline is strolling sincerely I must have shown that however that is presently strolling so this pipeline is always going for walks I should have proven that counts formerly however I overlooked that step however within the logs of this one can find that basically the logging for pub/sub says hiya three keys got here via my approach and so what it did is it ran for each and every of these keys that ran by means of this pipeline so that’s already performed let’s examine if we return by way of so earlier than we had a key here my delete key no results found so that’s been wiped away that was the key we delete it out my trade key what did i change it to real proper I flipped it from close to proper and the other is add and it can be there so so that is that’s with ease the whole lot of that pipeline it can be honestly a really rather easy pipeline whatever you might orchestrate pretty pretty effectively you propose to plant submit it as an answer in order that men and women can down load it and try their own so that’s it for me i’m going to hand it over to new okay so Sammy is showing you how to use data go with the flow as a streaming pipeline making certain your changes go from dynamo to spanner i will do the tremendous job which is the majority import creating the spanner illustration and int rating and importing the entire data so like we mentioned for clicks to click on create spanner i’ll create an instance i’m going to use the music brains yep spelled accurately database whatever you could figure it in my house country you are at West one which is Belgium however you’ve been within that information middle it’s large i I was expecting it to be a huge but it used to be better so we create twenty nodes this may occasionally supply us a database a good way to be ready to control forty terabytes of knowledge 2 hundred thousand reads per 2d and forty thousand writes per second and it can be a larger than what we want for musicbrainz database but it’s for getting the demos going down rapidly here we’ve our DDL which is simple create table you will discover right here that i am using a commits timestamp on that row and there may be primary keys i am using a hashed ideas the preliminary predominant key i’m going to provide an explanation for that within the subsequent part so i am just going to repeat paste this into my spanner creation proceed editors text BAM and create and this is my fourth click on in order that creates my database and thanks and there i’ve a hundred and something tables which might be in the musicbrainz database so now I wish to import my data good musicbrainz already places all their data on their website as tabbed eliminated layout export records so I put all those already in a cloud storage bucket I’ve written a dataflow job as Siamese explained with the entire steps and i am now going to run that dataflow job to pull the records frob within the supply route from this cloud storage bucket and putting it in this new database that I’ve simply created so simply copy that and run it and this simple build runs depth of maven and it began and in a few seconds it is going to provoke the dataflow job – commencing bulk importing the info yep however there goes in thought there we go so this dataflow job as Sammy defined earlier image nonetheless being analyzed there we go so it appears at this cloud storage bucket gets the list of documents to import it reads the tab delimited format files will get each line which is a single row in within the usual database you create the spanning mutation passing the info in that row changing it to the spanner varieties after which because it’s a batch job i’m going to batch these mutations together in organizations of 100 and and then write these batches of 100 to spanner it can be extra effective to write down batches of rows to spanner they just write character rows and this job is now going for walks its dataflow uses compute engine VMs and one can find right here if i refresh that web page it is created a bunch of VMs there we go a bunch of VMs to run these data go with the flow steps each and every of these packing containers will also be run on character nodes with dataflow managing the info passing between one and the opposite and it’s going to Rialto scale high and low to two and it can be just going there so it can be learn so far seventy eight records 234 documents and it’s opening to read them so okay we are going to let that go strolling and we will come again to the end of the subsequent section so Sammy mentioned no sequel and i mean after run by means of as speedily for the reason that now we have got much less time once we thought we had I imply talked about no sequel i am gonna be speakme about the relational database side import my deep may examples can be my sequel particular however the basic case applies to most relational databases so Sammy’s already talked about why and the benefits are reasonably apparent no planned downtime no ops the whole lot that’s managed for you operating procedure hardware and program updates occur all in the historical past horizontally scaled so you can simply add more vigor when you want to no sharding you’ve gotten bought a globally constant view of your data and outside consistency with acid compliant right transactions read transactions permit you to read information at a designated time stamp up to an hour old and you could have acquired all scott and c 2011 sequel queries so the very first thing want to do is seem at your present schema and examine the data types spanner has an awfully concise set of knowledge forms there may be simply this little bunch right here all of these can also be certainly used as keys aside from the array form the array style can you have any of the opposite varieties so you wish to have to look at your existing schema and map the existing data types to the cloud spanner knowledge types many of them have an immediate mapping however some of them as you will see that in this record don’t have a direct mapping on this case you want to alter the application database access layer like we recounted previous to convert out of your internal representation to an an identical spanner illustration so for illustration an email you would write that to spanner as a string and you pass it again out and theum in your software table keys are an essential consideration of spanner in average databases you most often work with sequences the place your rows expand simply consistently that is an anti-sample a spanner on the grounds that spanner splits the data in into more than one splits sorted by means of essential key and while you add information it is delivered to the split so when you’ve acquired a sequential key perpetually increasing it can constantly be introduced to the final break up and if you are doing that lots then your final bit turns into the one break up the place there’s any database endeavor becomes a hotspot and you will have 20 nodes but you’re handiest utilising one to jot down your data so what do you do about this good you have got to prefix your keys with one more key with the intention to distribute the information higher now if it was once a a Greenfield database you most commonly use a specific UID or random key but because we’re importing we want to maintain this sequential key so what will we do well we add a hash we without difficulty do a easy hash of the original key and prefix that in the span of essential case you see on the 2d row the fundamental key has a hashed id which in this case of just on a crc32 it doesn’t have got to be comfy it simply must be quite random however deterministic situated on the normal identification there’s tons of documentation on google comm about the right way to hash keys and other date details where to hinder hotspots in cloud spanner by via utilizing these this selection of path if you have referential keys you need to incorporate the hash key within the reference considering that it’s the principal key of the prevailing desk so you ought to incorporate the hash key in the referenced table that is to preclude a full-scale desk scan when you are trying to look up the keys whilst you do a join as soon as the application has been totally migrated you can do another migration if you want to which is to cast off the entire sequences and such the whole thing to detailed you IDs secondary indexes in spanner are additionally applied by tables beneath the hood so the certain alternate drawback happens with columns you’ve got received an index on this case we’re indexing events by means of timestamp timestamp of publications are regularly increasing in key and you’ll be able to get a hotspot for the reason that you are adding more and more movements increasing in time so getting a hotspot what do you do right here well you do have something known as utility-degree sharding which is creating a shard identification this isn’t the equal as a split id it is just an application defined value to combine up the information a little in this case i am making use of the crc32 of the timestamp modular one hundred which offers you a quantity from naught to 99 which is reasonably random established on the time stamp I had this into the table and i index on that timestamp shard identification in order that manner the index itself is randomly disbursed if I need to select from that index utilising a range choose I need to comprise all the shards when you consider that or else once more considering that it’s the key saina will do a desk scan so once more i’m picking out using the between flooring they are shards to not 99 and then using the variety clause and that gives a limited select and now not a full desk scan sequences don’t exist in clouds banette due to the fact that as I mentioned it is an anti-sample so for that you simply have to put in force them on your software the easiest method is to have a desk to your database referred to as sequences with a sequence title and the next identifier when you want so as to add a row to your desk you get the next identification you increment it and replace your sequences desk and then you definitely insert your new row with the certainly the hashed identification and the brand new sequence number that is first-rate for a hardly ever modified table but when you’ve bought some thing taking place so much this of course turns into a choke factor every each insert the place we need to wait on the sequences desk to do the replace we now have gone slightly too a ways for myself there so tips on how to preclude that may be to get each application instance control a block of sequences so the read say 100 sequences from the table control them internally issuing issuing the sequence IDs to itself it approach you can lose the steady value of the sequence to a targeted measure but as said steady keys are usually not the first-rate plan in spanner in any case overseas key constraints spanner offers numerous performance advantages by trusting the appliance to preserve the information steady and such a things is just not having overseas key constraints in different tables this that you can must put into effect in the utility if you need it however in most purposes it already is aware of what information is there what knowledge is not there and so that you wouldn’t be able to create applications isn’t able to create an object without the dad or mum object already existing for those who do want to add foreign key constraints which you could without problems do it your self in the database access layer without difficulty by checking for the existence of a reference table key and if it does not exist throw an exception and if it does then you definately insert your row and there is a international key constraint assess carried out utility aspect similarly on delete and on replace principles have got to even be implemented in the application on the grounds that there isn’t a overseas key constraints you find all of the little one IDs which are referenced with the aid of the mum or dad you delete all of them and then you definately delete your parent on that’s a non delete cascade rule of course on delete replace or on delete set now Knowle would be carried out via updating the rows or abandoning transactions will have to any little one rows be there as some you already acknowledged the interleaved dad or mum-baby relationship does have referential integrity constraints and on delete principles so right here we now have a guardian and a little one we now have told it to interleave and the mother or father on delete cascade Sammy’s acknowledged in element about that i am gonna simply pass over it but on this case there’s a foreign key constraint and the baby desk key have to reference the key of the mother or father and in a non-league cascade rule you delete the mum or dad at least the youngsters that you could create a hierarchy of six levels of tables in this method but given that the entire youngster tables have got to be within the equal split as a top-stage row the 4 gigabytes dimension cut up live it applies the scale of the highest-stage row and all its youngsters that hasn’t occurred very in general but i have had a purchaser that notion they would meet that drawback commit timestamps I stated you outline them in the schema with an choices clause in software you employ a certain worth to insert the commit timestamp and then you can use that throughout the migration method to observe whether a row has later or prior data i’m rather rushing through this since i can see the clock counting down fairly quickly other matters that you simply’d have to mention on the applying aspect default values handy to place in your to your database entry layer stored techniques and triggers good as a result of the distributed architecture triggers a little of an anti-sample you can without problems put in force in your application and seeing that spanner is without problems infinitely scalable you don’t have a worry about strolling triggers and stored methods and the database you just have extra extra nodes and everything runs better it also offers you the improvement that the saved systems and triggers you’re placing your business good judgment in the software with the relaxation of the code and you could have written in the equal language that you may unit scan it and without having a test database instance per table access privileges do not exist in spanner your entry manage is learn or write for the utilising the cloud platform i am controls for the whole database and finally sorry return JDBC it’s currently learn-best and there is no information amendment language currently but right at this second there is a second spanner speak going on over in Moscow any size the place Deepti are clarence minus PM is saying that data amendment language is being previewed correct now and there will be a readwrite JDBC wrapper coming quickly k we got a a minute or so left so let’s have a look at my demo and notice if everything is run k so again to the dataflow view what have we obtained so we have now read 234 source documents from that we’ve bought 20 million documents attain including to span at the expense of 31,000 per 2d batching them of course down to 300 batches per 2d or so and have a appear on the logged disasters there were no screw ups and 21 million successes and just to exhibit that that is for actual i will go stop this jobs to get my database of leisure where are we spanner let’s have a look at the artists credit score desk and let’s have a look at one of the vital information so right here when the information in the end comes out you lose mana the demo gods aren’t smiling on me with 20 seconds counting down on the clock there we go so right here we see that the info has been brought the fashioned sequential IDs have been prefixed by means of a hash and as a result being wholly combined up in a random order and if I just wish to run a question on that knowledge will run a simple query choosing all the recordings which have the phrase cloud of their name joining them with the artist and spot what we get out query however there we go this one is question this when I verified it the previous day took about 5 seconds for the reason that it is a demos however we will take ten times as lengthy and we will also be sitting right here speaking to myself for five minutes yeah so as soon as the question comes again having you scanned its a few million rows due to the fact of direction i’m not utilising an index key i am utilizing a table scan on the name k what we’ll do is we are going to let that run which given that the demo gods are absolutely not smiling on me would run via a quick final couple of slides and we’ll come back to this so other matters wrap up the next day there is a talk on how nest digital camera offerings moved to Google clouds they in the beginning on Amazon when Google received them they usually’ve simply accomplished a enormous migration so the entire camera offerings your entire recordings on nstor now on Google Cloud Niantic are going to talk about relocating to cloud spanner and now antic other persons at the back of Ingres and pokemon go and reinventing databases for your journey via the cloud within the archives from the day past there may be opti ver who migrated from Oracle to cloud and there classes learned bandai namco how they utilising cloud spanner and the session that i simply recounted see what’s new with cloud spanner which is happening right this minute in a restart my query because it seems to have got stuck just to irritate me and subsequently quote from decide eva after they move from Oracle to spanner they might approach ten occasions extra transactions at one tenth of the rate so they are certainly very happy with migration from all codes banner one other thing I identical to to announce is the next day which is cloud hero it is a and i here’s my cape due to the fact i am it sounds as if a cloud hero it is a increase kind game where you race in opposition to the clock to meet a element of challenges so I now have my cape and if we go back to the demo it has eventually completed its question we have a bunch of tracks with their artists who i’ve not ever heard of earlier than and and there we go that’s clearly blanketed it we’ve long gone a little bit bit over time i am sorry about that in case you have any questions how much time do we’ve got left no simply satisfactory it can be ok thank you ok [Applause] you [Music]
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