What's going on, everyone? Sam here, late in sports cards, we're up in 21, 22, Panini Mosaic basketball choice, 20 box, full case break number four, tiered random team style. Here's a look again at your random results. As always, you can find these on the website under the results tab, as well as the link that's in chat. So good luck, everybody. Let's do it, 21, 22, Mosaic choice, full case. See you later, Panini tape. And we'll see you later, Cardboard Box. Not the Panini tape. No. It's like inception, dude. Inception, it's impossible to get. Anything to stay up. I thought you'd done this before. I haven't though, darling. You haven't? No. So I guess we'll do like stacks of five, more stacks of five, maybe, makes sense here. I think that probably makes the most sense. See everything on the top of the camera, still. Alrighty. All right, there you go. So, box number one. Look here, guys.  Conaluka, that'd be awesome. Silver Mitchell. You got Isaiah Tad and Luca Garza on your exclusives. Malik Monk, first auto, going to the Lakers. Nice one there, Minsu. Malik Monk, Kentucky legend. Now to 88 is Pascal Siakam for the Raptors. We've got Chris Paul for the Suns. And Fakunda Kampazo for the Nuggets. It's full of Nebula. Liz, Liz, Liz, Nebula, Liz. Liz. JT Thor and Usman Garuba. Kevin Herter and Malcolm Brogdon. This is what I think it is. Still in Evan Mobley auto, I thought it was black gold. Nice one there, congrats Cavaliers. There you go, Tony P. And that is Evan Mobley on the autograph. Very nice, we'll take that. To 80 is Shreyman Green. 88. James Bookknight and Kelly Olynyk. Nice ones there. Peacock, come on baby. Herbert Jones and Jalen Suggs. Something big, Peacock. Why not, why not us, why not now? Matisse Thible, John and Kaminga Mosaic Rookie. This one here, we've got going to the Hornets. That's gonna be Del Curry, that's awesome. Father of Steph and Seth. Is her dad any good? Yeah, he's pretty solid, he's a good shooter. I mean, understandably so. This one here is gonna be a black gold, Keldon Johnson for the Spurs is seven of eight. You can recap the black gold, see if that's cool. There hasn't been any others than just this one right here. Drew Holliday is gonna be your exclusive to 88 and Peacock, Demarda Rosen. Nice one there for the Bulls. Really cool, same, good job. Congrats, leave me, Peacock's cool too. I thought you said let's get a Peacock right now. That worked out pretty well. We're also sold out in the night, thank you everybody. Appreciate y'all. Another Peacock, Brandon Boston Jr. and Corey Kispert, Silver Gary Trent, Mosaic Alex Baruso and Omar Yurtsevin for the Heat. Nice one there, Clint Omar Yurtsevin. Doesn't have a lot of autos, that's pretty nice actually. Congrats on that. Got Brandon Boston Jr. to 88, Desmond Vane to 88 and Peacock James Harden. Nice one there for the Sixers. Congrats on that Philly. Going to Scott M. Again, super short printed Peacock, James Harden, Fear the Beard. Oh, that's good. I don't fear the beard. The next one, Jared Butler and Alfred Shengun on your exclusives. Silver PJ Washington, Mosaic Evan Mowley debut. Nice one there for the Cavaliers. Got going to the Lakers, Avery Bradley. Nice one there again, LA, picking up another auto. We've got Julius Randall to 88. Hey, Herbert Jones, Rookie to 88. It looks like a black gold on the back is Herbert Jones. There you go, Pelicans. Six of eight on the herb. Going to Eric W. Congrats, Eric. Nice one there, buddy. Herbert Jones, Rookie. A lot of bull. What is a flower, what is 4.4? That's fast. Geez, dude. Why is E.J. Manuel making pro comps? Cause why not? Yeah, it's like anybody do pro comps now. Theron Sharp and Joshua Primo. They had nobody else. I guess not. Crystal Orte silver, Danny Green. There's Brandon Boston, Jr. Rookie auto for the Clippers, BB. We've got another Peacock coming up here, guys. That's going to be Steph Curry, National Pride to 88. Lexi Pokeshevsky to 88 for the Thunder. And Peacock, Isaiah Todd. Nice Rookie there for the Wizards. Tier two from Michael M. Congrats, Michael. Who breaks? That's a little orange there. Yeah, not very big, very big order. Jonathan Kominga and Greg Brown, exclusives. Exclusivos. Silver, Joellen Bede, Mosaic, Julius Randall. We've got the Humana highlight reel going to the Hawks, Dominique Wilkins. Nice one there, Tony on your tier two. Nice one here, going to the Bulls, Black, Gold, Lonzo Ball. Two of eight, that is Jersey numbered. Congrats on that, Chicago. Eric W on the tier two hit. Grads, buddy. Got Yusuf Nurkic to 88 and Seth Curry to 88 for the Blazers and the Nets. What was AI's nickname? The answer. I thought he was human highlight reel for a second. Yeah, now he's AI in the answer pretty much for most of this career, yeah. Dominique's the human highlight reel, which I love. Franz Wagner, Chris Duarte, exclusives. You've got Moses Moody, Taylor Horton Tucker. Our auto, Wendell Carter Jr. Nice one there for the Magic. Wendell Carter Jr., going to Orlando, Alvin S. Got to 88, Chris Duarte for the Pacers. Grayson Allen for the Bucks. And Kyle Lowry for the Heat. Kai Jones, Trey Murphy. Got Silver Jah, Jordan Nora. It's going to be a Miles McBride. Nice one there for the Nicks on the Rookie Auto. You've got Jeremy Grant, five of eight on the Black Gold. I swear to God, I think I pulled another one of these Jeremy Grant Black Golds. Nice one there for the Pistons. Jalen Brunson for the Mabs to 88, and Terry Rozier for the Hornets to 88. This is the second one you pulled? I think, I'm pretty sure I pulled another. For some reason I remember that. So you pulled a quarter of the... Yes, of the Black Golds, Jeremy Grant. Interesting. Yes, yes I have. Well, if you pulled the other six. That'd be wild, I hope I do. The interesting stat. Be my boy on McDonovich from Spectra, because you weren't top loading yet, but I'll tell you right after this box. Josh Christopher and Evan Mobley. There's Silverziar Williams, Mosaic, Cam Reddish. Auto is gonna be going to the Hornets. That is Kelly Ubre, Jr. Nice one there, Charlotte on the tier two hit. Apology. We've got to 88, Sidique Bay for the Pistons, Yanis for the Bucks, and Cade, National Pride for the Pistons. Nice little box there. So when we were doing Spectra group breaks for basketball, Boyan McDonovich, he was on the jazz in that product. He's on the Pistons now. He's just a really good shooter, he's like a guard. Has three cards in the set. Three autos. No, three cards total in the set. He has one of the autos of him on two different teams. Then he has a base, and he has one other autograph, and I pulled two of the Nebulas. Two of the Boyan McDonovich Nebulas. I pulled the base Nebula, and the auto where he's on two different teams, Nebula. So you haven't pulled all five? If not, there's only, what's it called? There's only three. I pulled one of ones. What do you do with your spot? Doddum and Mitchell, Davion Mitchell, Jayden Springer, if I did, I just meant to say he only has three cards in the set. Clay Thompson, Luca, Mosaic. See him forgetting how to count again. I guess so. Jalen Johnson for the Hawks. Nice one there on the rookie order. Got Nick Claxton going to the Nets to 88. Kevin Porter Jr. to 88. And Cam Thomas to 88. Nice, Nets. Charles Bassey and Jared Butler. Silver, Davion Mitchell, Laurie Markner. This'll work. Going to Eric W. How about a Steph Curry? Boom. On the Mosaic auto. Congrats, man. That's awesome. There we go, Eric. We'll get that magged up for you, buddy. Congrats. We'll take a Curry all day long. No, Chad, we should have some room tonight. There's Ivika Zubak to 88. Hey, Davion Mitchell to 88. And Paul George to 88. Nice box there again. Take a Curry for sure. Yeah, there should be a Seth auto in here too. We got Dell and Steph. Oh, we need to get a Seth auto now if he's in Nets. I hope he is. Oh, that'd be awesome. Quentin Grimes and Austin Reeves. Danny Green, Silver. Jalen Suggs, National Pride Mosaic. And Otto, Facundo Campazzo. Bass Otto going to the Nuggets. Nice one there. Denver. We've got Quentin Grimes to 88. Spencer Dinway to 88. And Alex Caruso to 88. Trayman and Isaiah Jackson. Silver Hamedu Diallo. Mosaic, Jeremy Grant. And Otto, Karris Levert going to the Cavaliers. Nice one there. Karris Levert. We've got to 88. Cat, Jose, Jay Crowder to 88. And a Trey Murphy to 88. I want to see Nebula so bad, dude. Or just keeps hogging them all. What one then? Tryin', dude. One. They're one-on-ones. There's not more than one of them. Do better, Sam. We'll tolerate this any minute. Jalen Johnson. And Jalen Green for Jalen's. Seems like I wish I was here. Silver, Jalen, Orton, Tucker, San D'Aldo, and now for the Grizzlies on the Mosaic. And Davion Mitchell, Rookie Auto for the Kings. Nice one there. Congrats. Defensive Menace, Davion Mitchell. To 88, Matisse Thible. Ruge for the Jazz. And Julius Randall for the Knicks. Now when you say Mitchell's a defensive menace. Yeah. He's actually, like, primarily a better defender than he is. Yes, now that is actual, like, yeah. I can't tell what he's doing. He's got a back check, that's all. There. Keon Johnson. And James Bookman. I don't think so, David.  Silver Bobon, Bones Highland, Mosaic, Rookie, and Zyra Williams, Rookie Auto going to the Grizzlies. That's one there at Memphis. The Bitcoin 101 sitting there somewhere. Bitcoin. Got Buddy Heald to 88. Davion Mitchell to 88. And Eric Gordon to 88. He has nicknames Off Knight, because of how good he is defensively. Oh, yeah. So he is really good. That's why, like, he was a, well, he was a senior when he got drafted, right? There's Io Dasunmu and Moses Moody. Like, he was like a 22-year-old rookie or something. And he literally went in the lottery because of how good he is defensively. Silver Evan Mobley. Clay Thompson. We've got Josh Giddy. There we go, Thunder. Congrats on that. OKC is going to be going to Scott M. Congrats, Scott. Yeah, I think he was a senior when he got drafted. Scotty Barnes to 88. Nice. So what, the Giddy up to 21? Nah, if it was a black-gold, sure. Frank Jackson. And Jakub Pertle, 88 as well.  I don't dilute it. Oh, yeah.   Yeah. What do you think I am in it? Gotcha. What do you think I want to look like a fool, Donnie? Yeah.  I know they really have nailed the draft picks over the last three years. Too bad they traded Halliburton, though. Santi Aldam, Araldama, and Scotty Barnes. I guess not too bad, because they are the two seed in the West. Silver, Cole Anthony, CJ McCollum. Halliburton's on the pacer here. Yes. There's Luke Longley, nice one there for the bulls. See how I knew that. That's pretty impressive, actually. Right. We've got Luka Donchich to 88. We've got Zach Levine to 88. And Blackgold, Alexi Pokeshevsky, seven of eight. Nice poku going to the Thunder. I tried for you, David. I tried. Really? That's insane. He is so underrated.  So underrated. Can I say it one more time? He's underrated. That's how underrated he is. You have to say it four times to get people to listen, because he is. Zyra Williams and Dalin O'Benton. He barely made the all-star game, which is sad. Silver is Steph Curry. Matisse Stival. And Kenny Skywalker, Blackgold Otto, four of eight. Going to the next. Nice one there. Congrats, next. To 88, Jada McDaniels. We got a Blackgold. Steph Curry, National Pride. Boom, Eric W killing it with the warrior spot, dude. Four of eight. Let's go. Congrats on that. Nasty Curry. We'll go ahead and get that mag for you, Eric. Dalin O'Benton as well. To 88. Last box-o-choice. Good luck here, everybody. There's Aaron Wiggins and Cam Thomas. We've got Silver Laurie Markman. Mosaic, Trey Merkin. Our last auto of the break is Joe Keeb. Noah, nice one there. That's awesome. For the bolts, we've got Greg Brown to 88, a Bobon to 88, and a Dillon Brooks to 88. That'll do it for this guy. That'll do it for the break. That guy needs help. That'll do it for the break, guys. We'll do a quick recap.  Say thank you. Just eventually, we've got Blackgolds to eight, Poku, Jeremy Grant, Wanzo, Herbert Jones, and Kelvin Johnson. Autos, Joe Keeb, Noah, Kenny Skywalker, Luke Longley, Zyre Williams, Daveyon Mitchell, Harris Lavert, Fukunin Campazo, Jalen Johnson, Kelly Ubre, Miles McBride, Wendell Carter Jr., Dominique Wilkins, Rennan Boston Jr., Avery Bradley, Omar Yurt 7, Del Curry, Malik Monk, Magged, we had Josh Giddy, Evan Mobley. How about this little pairing right here? How about a Steph Curry auto and a Steph Curry Blackgold number to eight? Very nice. Congrats again, Eric, with the Warriors. That'll do it for the break, guys. Thanks again for the fill. Next up, we've got football.


Okay, as a constructive grant. Okay, so we're recording now so I, let's say it's 635 by my camera. So should I be announcing that at this point. Give it one more minute as long as it takes attendees a minute to. Oh, I see attendees has popped. They've all popped in a mirror. Everybody's here now. Right. Yeah. Do you want just for ease? Do you want to just give the spiel? Um, yeah, I was just saying, right. Amir was hoping to get an extension in. We'll have to see how that works out. Okay. I guess if you give it, I could just answer questions if anyone has any. So. For all our attendees who are here. Unfortunately, we were not able to meet quorum tonight. So we're not proceeding with the meeting, but the demolition permit requested. See if I get the language right here will go forward. I'm sorry, I forgot the phrase. The demolition authorization for 1240 Southeast Street will proceed as a constructive grant. Due to, you know, inaction or lack of action by the commission within the timeframe. Specified in the bylaw. So it, you know, staff. And the chair of the commission discussed it. We don't think it's warranted to. You know, try to extend the review for this. So it'll, it'll be approved. As a constructive approval. Okay. Anything else. No, I was going to say for Amir was hoping to extend. A demolition authorization for properties on Southeast street. And so. Without a quorum, we can't act. And so. Amir. I will talk to the building commissioner and we'll reach out to you tomorrow. About that. Okay. Do I want to ask if attendees have any questions to raise their hands before we adjourn? Yeah, there's nothing we can really discuss, but I guess if there's any questions. Yeah. Okay. So if anybody wants to raise their hand, feel free. And then our intention is to have a rescheduled meeting with them. Sometime in two weeks. Yeah. Okay. So. Do I, I'm just managing.  Just allowed to talk. Yeah. Okay. So I'm allowing Amir in here. Hi, Amir, go ahead. You're muted right now. Yes. I just wanted to know that. I hope that, you know, I believe by the way I understood the, from Chris. I just wanted to know that if you're going to meet in two weeks. That's, I'm here. This is Nate. That's. I have to check with the building. I have to check with the building commissioner. So. You know, we were able to, we were able to squeeze this in today, but we don't have a Cormorom. And so. I guess that I will reach out tomorrow. Yeah. After speaking with the building commissioner. All right then. Thank you so much. Thank you. Thank you. Okay. No other hands raised at this point. All right.  We'll try to meet, you know, within two weeks. It'll be a similar agenda for everyone who's listening. Yeah. Minus the hearing. Yep. Okay. Thanks everybody. Thank you. Thanks, Robin. Have a good evening. Bye.


I want to welcome you to getting started with PostGas and OpenStreetMap. My name is Lindsay Hooper. I'm one of the PostGas conference organizers and I'm so excited to be here on the line with you guys and with Ryan Lambert, owner of Rustproof Labs. A little bit on Ryan, he's been working with GIS since 2011 and he got his start in PostGas when on a quest to update a roadmap he started using PostGas, PostGas and OpenStreetMap. He's been a contributor to OpenStreetMap projects since 2015 as well. Currently he is working on a book on how to use PostGas and OpenStreetMap together and he's run, excuse me, he's run PostGas on both large and small scales and I'm going to kick it off to Ryan now so enjoy and Ryan take it away. Thank you Lindsay. Thank you Lindsay for the introduction and thank you to PostGasComp for hosting this session and making this whole thing possible. Thank you also to everyone who's joined us live today. It's great to have you here and we are also recording the session to make it available for future, for anyone who wasn't able to make it live today. I am Ryan Lambert. The best place you can find what I'm interested in is on our blog. I write about, publish something about twice a month. Most of it focuses on PostGas, PostGas related technologies and that ecosystem. I am also on Twitter if you want to follow me there. I talk about a lot of the same stuff. Ultimately I really just love technology and data. I've been involved with technology all of my life. I was lucky to have a computer in the house growing up and that really set the stage for me getting involved into a technology career later in life. I love PostGas and Maps in general which was one of the great things about finding OpenStreetMap was just the cool technology mixed in with something that I've loved all my life since the paper copies. So this is the first of what is planned to be a six-part series and this is the only one of the six that I would call non-technical and doesn't require some sort of background knowledge or the ability to be thrown into the deep end. The other five all get down into the nitty-gritty of the technology and the data and how to use them effectively together. But today we're going to keep it pretty high level. We're going to go over a high level view of the software and that's PostGas and PostGas. I'm going to go over the OpenStreetMap project that represents the data that I'm using and then I'm going to kind of show some examples of why these tools together make such a great pair in your toolkit and then to end it off I'll have a few examples that illustrate how spatial data looks when you put it into a relational world of SQL. So all of this is made in possible because the whole ecosystem that we're using here is open. The software is open source, PostGas and PostGas are open source software. OpenStreetMap is open data with the addition of open source software as well and this really opens it up to anyone and everyone who wants to get involved with spatial analysis. Before I can really jump in and explore what PostGas is, I need to set the stage a little bit with what a more traditional workflow with spatial data might look like. This is how I was introduced to GIS work and spatial work was we had really powerful cool desktop software that connected to a whole bunch of data on our file server. A file server was required for us because our data was considered sensitive and we had a policy that said you can't have it on your local drive. So we had a file server that allowed us to store all of our shape files and our attribute data and geodatabases and all of those goodies. The downside of this traditional model is that you're limited on what you can do and how you can scale and to start with the file server really is simple storage. It's nothing beyond your basic storage layer. It doesn't give you any other bonus or benefit or feature beyond storage and one of the side effects of having your data on a file server especially when working with a team is you end up with a whole lot of versions of the truth. You have a copy and paste of each shape file for specific projects. You might make a project specific change in one shape file and now you have multiple versions of the truth and this just seems to be encouraged by the use of a file server. There's also limitations to how granular you can make your security model. You in general file servers are granted permissions in wide swaths based on user groups or functional groups or permissions like that but the granular access simply is not there for row-level data and so that's one of the limitations if you work in an environment that has security compliance requirements and then in the world today the desktop software is only one of the components. We have so much on the web and if you want to put your data on the web linking your desktop software to a file server probably isn't the right route. On the desktop side of that traditional model we have some other limitations. My desktop is only so powerful. I have a quad core cpu and 8 giga ram. You might have 16 or 32 gigabytes of ram. You might have a faster processor with more cores but really what you can put inside your general desktop is limited. It's also competing with the human that is using the desktop namely me. I have 42 tabs in Chrome open at all times. I also probably have a virtual machine or two running few other soft pieces of software running and so if you're relying on your desktop to provide the oomph for the processing power it is simply just limited and some of these processes that you will run with spatial analysis and spatial data are very heavy-handed. They require a lot of power and when you when I do something like batch geocoding a large set of data I hit play watch it for a couple minutes to make sure it doesn't crash right away and then I had to go take a lunch for like two hours because it's going to take two or more hours to run some of these big processes and I can't do anything else with that machine until it completes or I risk interrupting the process and crashing it halfway. Another side effect of having all of your data on a file server and all of the processing in on your desktop software is all of that data has to go back and forth between the two. This is especially true if you are also updating data not just reading data you have to read the data off the file server your desktop software makes a change to it and it sends it back to the file server. This might or might not be a big deal depending on your environment. In my case I had my desktop was physically a quarter mile away from our data center on the same campus one building a quarter mile away with all of the ethernet and switches in between the latency was a killer to productivity for me. So having to send all of that data back and forth just to do simple processing isn't the best use of the resources of the network bandwidth. So to overcome these problems this is where we introduce post-GIS and a database server in this case post-grace. We feed our data into a single database our single source of truth we can consume all of our shape files all of our CSV files and honestly those CSV files were probably in the database to start with. You only put them to CSV files to get them into your desktop software. So you have your database that has all your data now and we can move over a lot of that processing. A lot of the stuff that the desktop software previously had to do our our database server our spatial database server can handle all of that. We can do the joins between feature layers you can do joins to attribute layers you can do analytics all right in the database and connect to it from your desktop. This allows you to you can still do spatial analysis from your desktop software nothing limiting you there but this allows you to choose which analysis you want to do on the desktop and which you want to offload to the server and really lets your desktop resources focus on on some more specific tasks. So post-GIS the official definition is up here. I like to just say that it adds superpowers to your existing relational databases so it really does when you see the plethora of of power of features and functions that are made available through post-GIS. Whoa that's a lot of cool stuff. One of the key words in the official definition up here is they call it a spatial database extender and that's a key component here because post-GIS really does sit on the shoulders of post-grace. It is an extension that takes advantage of post-grace's innate ability to be customized. That was a goal from day one with post-grace was to make it easy to to modify and customize to your needs to your workflow and post-GIS took full advantage of that and continues to reap the benefits. So post-grace is a standard relational database management system. It is open source. If you hear the words open source and you think uh oh I can't get support that is false there are plenty of organizations out there that will provide you enterprise level support for your post-grace databases. So just because you hear the words open source don't think that it's going to be unsupported and a big headache because it is not and it's a really great community both in the uh the companies that support post-grace and just the wider open source community as a whole. Being a relational database post-grace is going to take really really good care of your data. It loves your data and it's going to make sure that it comes in and it keeps it very well protected. You get all of the wonderful benefits of a relational database. You get the easy SQL querying. You get to know that your data is consistent and reliable. You get transactions. If you need to scale up and have more power so it runs faster easy enough you can scale horizontally or vertically. You can do streaming replication and set up read-only nodes at different physical locations for fast read queries. Load balancing is really the sky is the limit with what you can do with post-grace and the existing ecosystem. And all of this lives underneath the post GIS functionality. We're going to focus in a little bit more on SQL querying. This is a really big benefit. This talk here, Lucas Eater gave a talk about how Java programmers would have to program a task to get some data out versus how SQL programmers do the same thing. And he calls it a he uses the terminology fourth generation language. In most intro SQL courses we refer to that as declarative programming language because you get to say here's what I want. And you don't have to think about how it gets it.  And I like to relate this to a manager and an employee kind of relationship. A manager that has a good employee they can say you know I really like you to get this task done for me and I need it fast. And if you have a good employee they can go out and they can do that task if they're well trained and they can come back and they can give you the result from the task. You as the manager do not have to necessarily ask hey how did you actually get that? And most times the manager shouldn't care how they got that. That's the way it is in SQL. You don't have to care about how you get it. I catch myself sometimes writing things in Python programming language and I start writing these weird loops and then after a few seconds wait a minute do it in SQL because SQL in in a nutshell is fast and productive. Not just on the server side and the technology side but it's fast and productive for the human side. You don't have to go through a whole lot of brain damage to think about what you want and how to get it. You just have to decide what you want and let the database take care of the rest. And this is especially true with spatial data where it can take advantage of these of the SQL syntax wonderfulness. So if you're familiar with relational databases in general but not so much with PostGrace this is a are a few things that PostGrace has that really adds some sugar to it. The hstore and JSON at the top I put that at the top because OpenStreetMap relies heavily on the hstore data type. And that allows us that's an extension another extension in PostGrace that allows us to store key value data that OpenStreetMap uses. And we use that in OpenStreetMap for historic reasons because JSON is a relatively new implementation in PostGrace. It's getting really really good with version 12 but for historic reasons OpenStreetMap still uses the hstore extension. Row-level security going back to the file server and the broad swaths of permissions that you can grant. Row-level security in PostGrace allows you to write SQL code and make that code a policy a security policy and apply that to your data. So your security policies can use the data itself to decide who can see the data.  Maybe you only want the managers to be able to see their employees and not the employees of another manager. You can set up a row-level security policy that allows that kind of granularity of access. Really really cool stuff if you have a security conscious environment. Materialized views and generated columns. These are both ways that PostGrace allows us to decide to pre-compute some values and save them to disk. Materialized views have been around for a long time and it's a lot like a regular SQL view. It just saves all the data to disk. Generated columns are new in version 12 but it allows you to calculate a single row's value based on other data in that column or functions. Really cool stuff that allow you to offload the expensive portions of your spatial analysis. GIST indexes. That's what we would in this context call a spatial index and that's really what makes all the querying super fast. When you say I want all the coffee shops within five miles a GIST index can make that happen like things be.  When your data size hits over 8 kilobytes per row it gets put into this oversized storage we call toast and it automatically compresses it at the same time by default. You get some storage size benefits there as well. Just some cool extra benefits that PostGrace brings to the table and because PostGIS is an extension it gets to stand on the shoulder of a giant and by putting our data in the same database with our spatial processing PostGIS we get to cut out a whole lot of network back and forth and all of the latencies that are attached to that. We have our data and our processing in one place makes it super, super efficient. If you're familiar with spatial analysis you may be wondering can PostGIS do what you need it to and the answer is probably without knowing everything that you're doing. I can't say that in advance but there's a really good chance that it can already do what you need. One of the fun things about talking about PostGIS is every time I show a specific way to do something after the fact someone will come up to me and say why did you do it this way instead of that way and my response is normally huh I didn't know that way existed let me go see if I'm doing it wrong because there's so much power and so many options inside of PostGIS it's hard to know everything and the best and the always the best method for your particular task. In PostGIS if you look at the function count that it installs it's over 1,300 functions that get added to a database when you install the extension. One point to know is that with PostGIS 3 the roster components of PostGIS have been split out so in PostGIS 3 if you install just the vector base the base vector portion you'll have a smaller number than that. Any time you put data into a system one of the natural questions to ask is how do I get it out. With PostGIS we have no shortage of tools to use I've been talking about the generic desktop software so far we have those are those are really good options they're on the heavy-handed side if you're a database person though so you might not want to be writing sequel queries and those. Luckily we have some specific tools for the sequel lovers of us. D. Beaver and P. G. Admin 4 both have introduced spatial viewers in the past year or so. The spatial viewer allows you to write and draft your sequel query your spatial sequel in an easy editor and then you can select some or all the data and visualize it in a map. Really cool and really handy for those of us that need to write the queries but also want to visualize the data at the same time. And then for the developers if you want to be if you want to write something on a web layer or in a programming language there are plenty of tools for the variety of languages and frameworks of your choice so you can probably get get in touch with the data. And of course all of those DBAs in PostGris land that love PSQL and swear by it no problem they can use it too. Again with interoperability there are plenty of formats that we can work with. If you have your spatial data in your database you can wrap a query up with the as GeoJSON and you'll get a GeoJSON dataset. If you need a well-known text representation there are multiple functions for that. Shapefiles no problem those are unfortunately command line tools I don't know of a way directly in SQL to do that but there are ways to interface with shapefiles and all of those others. And one of the coolest I've seen lately is the ability to create a full-blown tile server in PostGIS. So MVT that is stands for map box vector tile I believe and so this post by Paul Ramsey goes through the steps that you can do you can take in order to stand up a tile server in PostGIS. And then one more point I like to throw out there about PostGIS is we are not in any way restricted to earth. In this talk today in this series we're talking open street maps so that obviously puts us on earth but if you're in other fields that have spatial kinds of data you are not this PostGIS is a good option to consider. I know the European Space Agency gave a talk last March in New York about how they are using PostGIS and Green Plum. An example teaching datasets are a good example of when you might want to not bound something to earth because it's a whole lot easier to use simple integers instead of real latitude longitude values. So on to open street map so this is the data side of things as I'm seeing it. I do need to throw out there though open street map is not limited to just data. The ecosystem of open street map has its own software and interfaces and there's a whole lot going on here but for the purpose of this talk I am focusing on open street map simply as a data source. So if it just so you're aware that I that it is larger than what I am showing in this context that we are just concerned about the data for right now. So open street map is a really cool project it's been around for about 15 years started in the UK and it represents a global dataset and this is one of the reasons I love open street map as one of my core base datasets is because no matter where I want to work you know geographically on data I can at least get a starting point from open street map. I know of a number of US specific sources for this and there's European sources for that open street map is a global data source so that gives us a kind of a consistency consistent starting point that is nice to work with. It is a semi-structured dataset that goes back to the age store data type I was talking about earlier it's a they store the data in key value pairs and if you're familiar with semi-structured datasets you might be fully aware of the pain that this can cause on the reporting end of things because with the flexibility up front makes for more work later on. So the official definition of open street map is up here I can never seem to remember this whole blurb when I'm talking to people on the street so I just say it's Wikipedia for maps. That's about the most succinct way I can say it and most people understand what Wikipedia is and the important concept that anyone can edit is which makes you either happy or nervous depending on on where you stand on that topic but it's basically Wikipedia for maps people around the world create accounts and sign in and make changes and make it a better place. Open street map is used very very widely if you have seen a map that is made by anyone other than Google is most likely an open street map source for that map. These are all over the place and its popularity has continued to grow over the years and this list of who's using it continues to grow which is really encouraging to see that the community itself is growing. So open street map itself when you look at it in a browser hey it looks like a map. This map has a few differences though namely in the top right corner there's a sign up feature.  So if you don't like what you see in the map you know it's wrong there's been construction recently that you're aware of you can edit and make it better. When we're looking at a map like this just think a little bit about how much data goes into making a map like this. How many data points does it take? Under we have city names that show up there's some forests the Rocky Mountains are off to the west there's a whole lot of information that has to be represented to draw a map like this. Every pixel that is here is here because of data in a database somewhere. That's pretty cool really at least to me but I'm a nerd like that. So open street map has a whole lot of data this is a very incomplete list of elements that you can find in open street map. These are some of the more common elements that most people will find themselves using at least once or twice in their career but there are everything down to fire hydrants trees and crosswalks in open street map. It is a unstructured semi-structured loosely regulated data set so you can put in a whole lot of random things that might not apply to everyone but they apply to your locality. When the data goes into open street map it's a it's done in a key value pair. This is an example of what a sidewalk might be keyed as. The left side of each equal sign represents the key and the right side of each equal sign represents the value. One thing to point out here is you might notice that some of the values can also be keys. In the case of footway we have highway equals footway so we're describing a kind of highway as a footway and then we can further describe that footway as a specific type. In this case it's a sidewalk and then we can have other attributes that explain what type of you know the surface paved or maybe surface equals dirt can go in there. There's a lot of information out on the wiki and if you're going to be consuming open street map if you're editing open street map you absolutely need to be here. If you're consuming open street map I highly recommend you get familiar with this wiki because it is going to help you much better understand the content of the data that you are working with. One of my favorite things about this wiki I'm not going to spend a lot of time on here is they have pictures and while a picture for a sidewalk might not seem like it's really all that necessary as you start looking through the diversity of the data and what they mean in different localities these pictures can become extremely helpful. So the wiki this is your data dictionary as far as open street map coding goes so keys when you when you take these keys and you turn them into more of a tabular data set that we're used to in in database land your keys then become your column headers so in this case we have our key highway has turned into a column header highway we can see that there's footways and residentials and other classifications of highway. Also I've included a max speed column not every row will have a max speed even if they should have a max speed they don't always get set and that's just one of the nuances that you have to understand with this data is that it's going to be partially completed in in various places. Going back to the volume of data this is a 3d map provided by this f4map.com they have this demo site this is a fully navigable 3d map using open street map data I'm not going to do a live demo of it during this because it takes a whole lot of oomph to run this in the browser and I don't want to risk that so I have this screenshot to kind of illustrate how much data is here and so this is we're looking at Coors stadium Coors field in downtown Denver this is where the Colorado Rockies play and to think about how many attributes and how many polygons and points go into making the 3d representation of a stadium is just mind boggling and then you know you look at we have flags up here on this ridge we have all these trees around there's uh street lamps in the parking lots and stuff this is all data in open street map there is a lot of information here that you can that is at your fingertips and is freely available for you to take advantage of as the number of tags grows they they don't each get their own column in the database as I've mentioned we use the hstore data type to shove all those key value pairs into a single column in this case I've ran a simple sequel query where I'm filtering for the Coors field that's the polygon we were just looking at at 3d and I'm grabbing it from a table and then I'm splitting out the keys the key value pairs that are all that are in that file or in that column and we can see down here the diversity we have ellie that's elevation 1585 again the wiki will tell you that this unit is supposed to be meters but so if you don't know what unit something is in the wiki will help you out there we have a website for where to find the information on mlbu.com we have a wikipedia name we have roof color in hexadecimal and color is a good thing to point out going back to the beginning of open street map remember it was started in the uk so all of us in american english spellers will have to relearn how to spell a few words in order to work with open street map but this here this isn't even the full list of of attributes because my screen is only that i can share is only so big there are so many attributes on in this data that you can take advantage of in any type of analysis that you may be doing so the spatial data we're talking about when we talk about open street map data is called vector data and I briefly mentioned that earlier about the split between vector data and roster data but we are dealing with vector data and in a nutshell that's points lines polygons and then the multiversions of each of those but that's what says this is a point this is a polygon it's next to that line that's how the the spatial information but then as we've seen we have this amazing wealth of semi-structured pairs of data so we have so much information that we can work with here you can use open street map for a whole lot of things as was mentioned I got started with I just wanted a roads layer the roads layer we had was horribly out of date it was horribly structured I just wanted kind of a clean slate for for some base maps and that was where I discovered open street map and ultimately how I discovered post grace and post gis before that I had worked in other databases but this was my first exposure to post gis was when I wanted to create that roads layer the 3d rendering is really really cool that that a four map site I reckon if you have some time to kill just go to somewhere you're interested in and zoom around and see what kind of 3d map you have in that area I'm hoping to see more and more development going into that that side of things and then analysis is really an open-ended box what do you what do you mean by analysis well it could be a whole lot of things so there there are so many things that this data set can be used for the your imagination is really the limit now when you want to get your hands on open street map data to use it there are a number of ways and the osm wiki has a whole page dedicated to this you can get the whole planet as one big file the compressed version of that in pbf format is over 40 gigabytes and it grows enormously when you decompress it and load it on the the open street map page in the browser that I showed earlier there is an export button that you can click for that you can get will allow you to grab small areas of data at a time there's an api that you can interact with to get to get data out and then there are other extract services such as geofabric that they provide regional extracts and that's actually the one that I have used the most I normally want larger areas of data so the browser export really isn't an option and in all in all reality I kind of just want to colorado to start with or I want all of the us I want a big region normally and so that's why I go for these regional extracts geofabrics service is really awesome they had they update their data sets basically once a day they have regional exports for the entire world by large and small region alike and pbf format is the most common that we'll be working with their download page looks about like this this is a small portion of their download page you know take over to the the main site and so we have our open street data extract page here the listing is down below with multiple formats so some files have more than one format depending on what they've decided to do I'm not sure how they make that decision what I do know is every region has a pbf file and that's why I've focused on using the pbf exclusively is because I know that I wherever I want it for I can get it north america the pbf is 8.8 gigabytes europe is 20.6 gigabytes these are not tiny files by any any stretch of the imagination if I click on north america and before I click on it notice that the map on the right hand side will overlay with a red color where you have selected so you know kind of what region that you're getting when you download something if I click into north america there's a few helpful bits here first is up at the top it'll tell you when it last was updated so I can see now that this was updated 19 hours ago if I was very concerned about getting the most recent data and I could wait five or six hours I would reckon I would wait five or six hours to get the next update if that was my my main goal scrolling down on the north america page we get all of the additional subregions within north america so if I wanted to download all of canada I can get all of canada without having to load the rest of the us and these are roughly split by state for the us and then down at the bottom there are some other special regions that allow you to they combine a handful of states together based on larger geographic regions and so depending on where you what region of the world you're looking at these regions and subregions will reflect those those areas so those those downloads I'm coming back to download size looking at north america this screenshot actually shows 8.7 gigabytes so it's grown 0.1 gig since I took this shot a couple weeks ago but the pbf size pbs are a highly compressed format there's a whole lot of information on the wiki about the format itself my eyes kind of glazed over as I got into it so feel free to dig in as much as you care to but the key detail here is the compression the compression ratio of pbf is 30 to 50 smaller final size than your other comparable gzip or other compression formats so that 8.8 gigabytes for um for the north america will be about 50 larger if you download another format of compression size and then once you decompress it and load it into post gis the data size is going to grow exponentially because of how post gis stores the data versus how the pbf format works so just something to be aware of on those file sizes that those are really really highly compressed files so we have once we've decided on a data source and we have our data in the downloaded we need to get it into our post gis database and this is done with a tool called osm to pgsql this is another tool that to the best of my knowledge is only offered in a command line option so you'll just have to run with command line and learn the switches the details behind this slide make up the entire content of the next session in this series loading data from the pbf format to post gis is quite a it's not that difficult but it takes a there's a bunch of steps you just have to get right and it's a slow enough process that when you get it wrong it takes a while for you to get those errors so you can restart if you are using osm to pgsql please it is in your best interest to use the latest and greatest version the ubuntu packaged versions are unfortunately quite a bit out of date and this project has been quite a bit quite active in the last year 1.0 was released only a few months ago and we're already up to 1.2 this latest version fixed a memory a memory bug that required a whole lot of RAM to load a little tiny bit of data so this you definitely want to be using the latest version of osm to pgsql and in a nutshell the the load process starts with your pbf file it's represented as this planet dump and osm to pgsql decompresses it parses it out and loads all the data into your post gis tables as necessary so osm to pgsql really is the gateway between your source osm data and your target post gis server and as i mentioned earlier this is a kind of a long running process this is from a blog post i'm not going to go into all the detail about the individual rigs or what this means beyond rig d the orange line was a digital ocean droplet one of the their new memory optimized droplets with 16 cores and 128 gigabytes of RAM with that in mind the north america load which is almost nine gigabytes takes well over an hour getting close to an hour and a half uh that's the orange line in the middle the far right orange line loading europe you can see that even that pretty powerful server takes almost five hours to load europe in full and that's just getting the data in it's really still kind of raw not fully ready to go yet that's just getting the data in so it is a slow running process it is a lot of data so be aware with of that so now why why use these technologies in this data i kind of feel like the whole talk so far has been covering the why but that's my nerdy technical side i'm seeing it so a few more reasons i think the most important and this is true with pretty much all open source projects is you can make it better and this is a really big deal i a while ago found a bug in and how post post grace handled xml data and it ultimately there was a long long known workaround to the side effect of this bug but because there was a workaround it really wasn't considered a critical bug to fix i got tired of of this workaround one day and i decided to dig in to see what i could do to make this better and it turns out i found a bug i reported it and six months later it was fixed in production if you have the latest and greatest version of post grace you never have to do this work around ever again i had a very tiny hand in helping fix that but you know it's what it's just really cool to be able to submit a bug and six months later it's in production it's fixed on the open street map side of things if you don't like the data you can make it better this is something i do on a regular basis i've i've made a goal this year to contribute more to open street map and other than the beautiful months of summer i did a pretty good job turns out i like to go play in summer and i i don't do very much mapping them but you can make contributions based on your local knowledge to make your data sets better a good visual representation of this is this is an animation i developed after hosting a mapping party in here in golden a few years ago the animation shows the open street map data sets over time and how the data filled in and you can go from a really blank slate and in a relatively short amount of time and less than a dozen people we filled in the bulk of the the core information around our local community so this is a visual representation of how you can contribute and complete make your data sets more complete another good reason it's the price is right there is no um entry fee to get into this club you you can just start playing today you don't have to pay out shell out big bucks and sign contracts and do a whole lot of stuff to get to use it it's just there and available this is a big deal especially for small organizations small businesses local governments etc and because of the price being so low there are only a handful of strings attached the only real one that i can think of is that if you produce results with open street map give credit where credit is due give credit to the the data set that made it possible to to produce the final results this isn't that hard to do and you can put it on your maps fairly unobtrusively and most people expect to see a copyright somewhere anyway another example of it's easy to use is the post grace license the post grace license is simple enough i can fit it here on a screen during the slideshow the simplicity of a of a con of a license might not be a seem like such a big deal but you don't need a team of lawyers to do an audit every now and then to see if you're in compliance because i can pretty much guarantee you are it's easy to use there's little friction these are all good reasons to use the systems another reason to use it and this is on a more personal note for me is you can use it for anything you want at any time and it's there and it's ready this blog post outlines a fire that happened very close to our house not too long ago here in golden on south table mountain and so the aftermath looked like this this was about three days after the fire had happened but one day my wife and i were both driving home at the same time and we both saw the same plume of smoke coming over the top of the mountain that we live right next to and we realized we've never talked about evacuation plans kind of a good deal this is also the moment we realized we have two cats but only one cat carrier so all this is going on and we're having these conversations we're watching the local news helicopters fly overhead us and on our tv we have the local news playing and i start making notes of where they're what what i'm seeing from the helicopter feed and before the the night was over i had a map of what the areas that had most likely burned and in the end result was i have a map of what actually did burn i went up and surveyed the whole area but having this open street map data i had all these data points that represent landmarks that i can i could correlate between what i was seeing in the aerial photography the aerial video versus what i know on the ground and what i can see an open street map and if open street map wasn't there and post gis didn't exist this is the kind of project that i could never have done and i would have never known exactly how far how close the fire got to our house it was pretty it was just over a mile so that was a really cool project and also to illustrate on the northwest of this map this is the coors brewery that's pretty valuable piece of property as far as golden is concerned we also have a country club over here that this fire was getting close to the wind had come up from the west and was pushing it up on the ridge and was getting ready to push it down the ridge into the country club and had the wind switch to come from the north this is all residences and mixed government commerce all of that so there's fire in the middle of a heavy heavily populated area i was able to quickly kind of see what is nearby what's impacted and where are we in relation to that another big benefit i love this one this is one of the my best selling points of post grace in general is you can run it on anything whatever hardware you already have whatever os you're already running you can probably run post grace on it if you have heavy powerful iron servers that you want to put it on cool it'll be fine you want to run it on a raspberry pi that's also cool it'll run fine you just have to have a little bit more patience because it's not going to be quite as fast but it will run so into some examples here we're going to look at so how spatial data looks in a relational world pretty standard simple sequel query we have the first line is says we want these columns the second line says get it from this table and the third line is our filter that says we only want to look at two boundaries we want to look at golden and we want to look at denver fairly simple this is a straight up you know standard relational query i wrapped it up here in a little bit of python code so i could execute it and show you the results i can run it and lo and behold i get a little table tabular results really nothing interesting here but it's just to illustrate the query now to take this another step we want to make it spatial enable we can do this i've added a single column into my sequel query called way this is the column that my geometry data is stored in my spatial data and by using adding this way data into my result set i can now use the geopandas tool and pull in pull this data in as a geodata frame from post gis and then i can plot it on a map so if i run this it'll run pretty quickly and right away i get a little square with a couple polygons the one on the left the smallest polygon on the left is golden the larger one on the right is the city and county of denver so this is not a very exciting spatial query but it is a spatial query nonetheless now this is where things really get interesting this is where things get fun spatial joins are one of the key components of spatial sequel just like any regular joins are a key component of any relational database the ability to join between tables is pretty critical this allows us to do those joins based on where they are in space in this case i'm now pulling from two tables i have my boundary polygon still that has my city i have aliased it as city we also and we're joining to a layer called natural point and this has some natural elements in the world around us and i'm i'm putting in there that i want to find just the trees more critically is the st contains this is the part that is post gis this is what allows us to do the spatial join we're looking for n dot way that's our trees layer we're looking for trees that are inside our city so with this again i'm wrapping up in a python so i can run it i can run this and now we get a series of points back this represents all the trees that are mapped in the city of golden if i want to change this and instead of maybe i don't want gold and maybe i want lakewood i can change that query is simple filter i get a completely different set of trees back based on where they are in space and this is the basic setup of what makes spatial query so awesome and just uh for fun to prove that uh this does run very nicely on a raspberry pi this is uh what i've been running my queries against is post grace running on a raspberry pi with post gis 2.5 so even for live demo for small data sets raspberry pi is sufficient to run and able to run spatial sequel for us all right so that takes us to the end of my slides so thank you everyone for attending please get in touch with me after the fact if you have questions i will try to get these slides posted i've meant to have that ready before today but when i saved the pdf uh for some reason the images were not coming through so i'll get that resolved and get the slides posted here in the next few days hopefully as well as the recording of the video but thank you for joining us everyone and we'll go ahead and close things down have a wonderful day


Good afternoon everyone and welcome. This is Melissa Armo with a stock swoosh and here I am today reviewing Google so I'm already out of this Now that there's anything wrong with that because I made really quick money taking this trade I was long Google calls that expire Friday. I bought them here on the Tuesday No, I bought them. No, I bought them Monday. Is this Monday? No, this is here. No, I bought them Monday get out of them Tuesday today's Wednesday. Let me know what day it is My life is so busy. Anyways, I bought them Monday sold them Tuesday Now what was the reason for doing that because it had to move up yesterday And I had doubled my money in the trade of the profit that I took of it so that made sense and I'm realizing more and more and more and more that That's what I want to do You know, you can hold these trains these overnights and the options for longer And I've done some out for several weeks, but every day that goes by you're losing time value Sometimes you get bigger moves if you hold them if you have the patience to stomach it but I'm realizing that I may want to increase my risk per trade and Quickly get out because very often I'm taking these trades Very similar to my day trades these option trades and they're going right into the money. I mean that is how good I am Predicting where it's going to go immediately just like my day trades I just have I have an amazing skill to be able to predict where stocks going to go right a ways and in the long-term trend in between right now and the long-term trend is XYZ number of days and weeks and months or could be years and that's the thing if you are Someone that has to make money right away is then the best thing to do is to day trade with me Or do the options trades with me and get in the right entry with the right pick I have and get right out when you're up and that is I think what many traders need to do to be successful And I'm finding that I like to do that the best even though I can get bigger moves sometimes these options trades This this looks great looks like it's going to go up go up over 770 follow through we got two days left in the week I'm already out of it. Could I make more money in this if I held a little bit more? Yes, maybe but you know again I was up very quickly low stress and Easy money, which I find is the best So I'm very good like I said at predicting where something's going to go right away So I can take the trade and take the entry and have the pick I can tell is going to go to a certain number right away So that's how I'm doing these then I can also tell in the longer term where it's going to go For example, I know that Google will recover kind of looks crappy here right now in the picture in the last two months But it will get over this area of 780 788 790 787 90 really once we get over this area here at 787 85 The stock should look amazing again It's still in an uptrend, but it doesn't look so hot, but it's fixing itself Today is really actually very good because it it opened today fell drop dramatically into a cell set up And then flipped it down is over yesterday's high So today was really a big reversal for the stock, but you know to get through this bar here It's take it's definitely taking some time that was back a month ago But the reality is that once this gets up over that level of resistance The stock should fly and probably will make a brand new all-time high although I don't I don't see us necessarily doing that for the end of the calendar year. It's 12 7 we got till 1230 1231 whatever So probably the market, you know, will continue rallying and I in Google will rally too But I don't see this hitting up over, you know, 816 68 the last all-time high in this by 1231 But it will okay. That's the point. I'm trying to make so I can predict where somebody's gonna go right a ways on the day You're the next day Like you could have bought this today You could have bought this today when it flipped you could have bought it And you could have made a good amount of money on this today as a brand new trade Not just the one I did you can do the same one and just bought it today again and sold it today again Anyways, this here. Okay, we'll do this in the longer term just like I can see where somebody's going in the short term I can see where somebody's going in the long term, but between now and then what do you do? You wait are you just do the quick trades or if you're in something for the long term You have to be in it as a swing trade unless you're doing an option out for a very very long time And so I think the beauty of what I do in reading gaps because that is how I'm able to get the entries That's how I'm able to get the picks That's I'm ever to read price action because I taught myself how to read gaps and when you learn how to read gaps Right, you will get better predicting stock movements That's the point I'm trying to make the whole point of this lecture here for the last five minutes It's if you can become good at reading gaps gap analysis itself. You actually can Predict the directional bias the stock will go because you will get better at reading Charts you will get better at reading patterns. You will get better at reading price analysis price movement You will get better much much much much better at reading directional bias and charts and therefore You will be able to see things like I see them To take an immediate entry that goes right into the money in these trades And I have had a higher success ratio with that in the options really then the then the day trades It's like 90 some percent or something that I've had for these options to take it and go right into the money I think there was one that didn't in the last year so that I'm in this is crazy But I'm realizing that I really do like the fast money. I definitely can predict quick directional bias very well Where it's going to go right now next day and I'm also very good at predicting in the long-term trend But when it gets to that number when it actually gets to the number is an unknown factor and I guess that's the point. I'm trying to make can anyone ever determine that the time You know something when it will get there You can say well Melissa of course it's of course Google was going to go back to this number No, not necessarily it may not necessarily at all. I'm telling you it's going to and I'm telling you 820 825 838 358 50 Google 2017 and possibly beyond but but no the answer is no not everyone can predict that Because I've very often seen numbers on this charts and other charts to I'm just using Google as example the market I've really done a great job with though Telling you where something's going to go in a number that doesn't exist because there is no number over this high here over 816 68 on the chart anywhere anywhere at all Okay, and it and no one's saying it has to go even back to that number the chart could break it could fall It could gap down it could break it could fall and turn around and go into a downtrend that could happen That could still happen. I could be wrong. I'm not going to be but I could be wrong Okay, the point I'm trying to make is that Without an analysis or correct understanding of what? Institutions are doing with the chart. It's hard for anyone to predict you can say well Go long on support and short resistance, but there's a million support resistance levels and that is in a strategy It's reading what the institutions are doing and who's in control of the stock that tells me ultimately When the control is continuing or when the control has flipped which sometimes it does people Okay, sometimes the control flips in a gap and this is where The analysis comes into play of the 26 points Which is what I do and the reason for my success and the reason for my student success Hope what I said today makes sense, but more and more realizing I Do exceptionally well with being able to predict where stocks are gonna go right a ways and in the long term is very unusual It's very unusual that I can do both very very well But I can't predict the timing of the long term when it's going to get to the number And I don't know if anyone can maybe someday. I'll be able to do that if that ever happens Boy, I'll really be a genius For now, I'm just gonna keep doing what I'm doing And I'm making the calls in the long term and doing the short-term trades as I'm doing here to make money for myself and my students But I will tell you that is all based on reading the gap and that is how I was able to get to this point most traders that are Good traders are either good at one or the other. They either really really good at predicting long-term trends Can't predict short-term movements or they're really good as day traders predicting quick fast movements Or scalping and can't predict a long-term trend or where a stock will go to save their life. I have a very very Unusual gift that I can do both. However, I cannot predict the timing of the long-term moves For the short-term moves. It doesn't matter. I get in and get out the date I'm in it for the day trade or I get in and out the next day or the next couple days for the for the option trade So good luck everyone and congratulations to everyone did the Google I gave it to the whole list and everybody got it and if you want to sign up for the option letter You can basically if you sign up now you get all of 2017 and it's gonna be a big year I think 2017 I think it's gonna be a big year for for me for the stock swish and also for the stock market I thought the stock market would have a big year this year It did have a good year comparatively the way we open and closed or where we're gonna close But we didn't have as big of a year this year in the market as I anticipated and thought I think it's gonna happen in 2017 and I think now that the presidential election is over that has That will have a lot to do with it as well when Trump takes office Congratulations everyone have a wonderful wonderful day a wonderful evening wonderful rest of the trading week Email me at lonesetthestockswish.com if you would like more information The next golden gap class is actually going to have live trading and it'll be on a Sunday and a Monday December 18th and 19th the very last class of the calendar year of 2016 have a great day everyone and email me at molestethestockswish.com for more information


Maybe many of you know the controversy between Bill Gates and the car industry that is, I guess, more than 20 years ago. Today things have changed and computers and cars have well melted together. So a typical car of today consists of many, many microcontrollers, computers and whatever. So they are devices that can be hacked as well. Yeah, that is, of course, something that has security implications. And I know that the speaker who will talk today, by the way, his name is Tilo Schumann. Give him a warm welcome. And he is here with a really old truck, nearly an old time, I guess. I'm not sure if he does so because he knows what can happen with modern cars if there's a hacker around. But maybe he will tell you in the upcoming talk. So that was my part. I would say the stage is yours. Good luck and enjoy. Good morning. Good morning. I'd like to welcome you. And as he just suggested, drink more water. Yeah. My name is Tilo Schumann. I'm not directly involved in the car industry. I'm somehow connected to it. I'm working with Ken for more than 15 years. So I have to do with all the different industries which use it and I have some insights into it. But just to start with my talk, I've brought a little video with me. So you may know something like this. So that's just a random video I found on YouTube. You see he's connecting the key to the car. Obviously not working. And then we just having a simple small device connecting to a diagnostics port available in the car, available in every car basically. And you see he's just learning the key to the car. It takes a little while. And then magically, ignition works. And that's not something really new. We have this working for years. That's just one car model right here. It works basically for any car model out there. You can buy such devices for cheap in China and Russia somewhere else. So that's the things what happens when we have with car theft. So the question what I was asking first is what really what is car hacking? We have it lately very important in the media, but what is it really? If we look a little bit back, we will see we have these clubs, people who are doing performance tuning via chip tuning, replacing firmware parameters, stuff like that to increase the power on their engine. That's actually car hacking. They are reversing firmware and replacing to get more performance of their car. We have others which allow you to enable new functionalities. Personally, I drive a Volvo. You can buy from whatever side small devices. You can connect to the diagnostics port and then enable new functionalities which were originally not intended for the car. It works. But for that, of course, they had to reverse the firmware to reverse the functionality of the car. But that's something we have not in the media right now. Of course, that's something what we have in the media. You can display arbitrary messages on your displays. Just two years, almost two years ago at the 30C3, we had a talk on this at the conference. Automated corrections. That's what some people like to do to increase the value of their car. Of course, that's also car hacking. Key programming. That's what we just saw in the video for those thieves. And just lately, wireless unlock, enabling of the car. So, yeah, it's very common these days that everybody has a remote for their car. In the US, even with the remote, you can also enable and disable the engine, not only open and closing the doors. Actually, that's not allowed in Europe. So, no car make is offering this in Europe. But it's possible. It's available. And that's the thing what you can exploit, of course. And what the thieves are exploiting. But the new level is now coming with, yeah, you can do all this via the internet and you can access access on a website. And the first remote is not only anymore you have some kind of a wireless remote, but you are having an app on your Android or iOS or something else. You can do it on a website. So, every Tesla you buy, basically, you have access on a website. And you see on the website where your car is, what the charge of the car is. You can open and close the doors and stuff like that. And that's the new level because everything is available remotely. Yeah. But what's the reason behind how this happened? I said I'm working in this industry for more than 15 years. And the thing is, what is basically the heart of every electronic in a car was established somewhere in the mid-80s. In the 90s, there were coming a new network which was Linn, a local interconnect network. Because it happened that CAN was way too expensive for the automotive industry to connect simple devices. So, they wanted to have a simpler network. And then in the 2000s, we had other networks coming by which were a little bit more complex than CAN, which were a little bit more expensive than CAN, offered more data throughput, stuff like that. That's basically ByteFlight, which was used by BMW for some time. We had FlexRay, which is used in different cars from Daimler. And now we have Ethernet in our cars. It's called ProtoReach, but it's actually Ethernet. It's currently implemented in the brand-new BMW 7 Series. ProtoReach is a little bit different to Ethernet in a way that it uses a different physical layer. Different physical layer, it's required because it has to be more robust. It uses not four wires, it uses only two wires, unshielded. So, it should be cheap. That's the reason why they built a new transceiver technology. But on the other layer above, it is just plain Ethernet. So, what's the difference between CAN and plain Ethernet? Because all over the world, all over the media, there is no security in CAN. So, what takes CAN apart from Ethernet? Both are basically a broadcast transmission. Broadcast in Ethernet, of course, it was all those all Ethernet cables, these PNC cables, that was the original plain Ethernet. That was also broadcast, of course, these days with 100 megabit, with 1 gigabit, maybe 10 gigabit. We don't even have a broadcast network as such anymore because we have just point-to-point connection which is managing all the stuff in between. But if we have a broadcast connection where everybody is on the same line, how do we detect if someone is able to speak? How do we allow that someone is able to speak? And the difference is here between CAN and Ethernet. CAN is non-destructive. So, in CAN, always the most important message is getting through versus in Ethernet, if two devices are communicating at the same point in time, it may happen that both messages are being destroyed and have to be repeated afterwards. So, we have delays if we have collisions. That's not happening in CAN. What is the data definition used in those networks? Actually, in CAN, we have no data definition. In CAN, it is only defined, we have eight bytes of data to be transmitted in future with the extension of CAN where we are currently developing on it's possible to transmit 64 bytes of data, but we are only defining to transmit data. We are not defining the structure of the data, what the meaning of the data is and alike. And to be honest, we don't have that in Ethernet at all. We don't have those kind of definitions in Ethernet. A de facto standard has become on Ethernet TCP IP. But if you remember in former times, we have different definitions on Ethernet which was Net Buyers, Apple Talk, you name it, all those different things. These days, we have only a de facto standard which is basically TCP IP. And we don't have this de facto standard in CAN. And the same is in security. Of course, we have no security in CAN because we have no data definition. That's the same in Ethernet as we have no data definition of Ethernet. In Ethernet, we have no security in Ethernet. The security is not even in TCP IP. It's a little bit above of TCP IP is the TLS layer. So you see, CAN and Ethernet are somehow comparable. And the use case, of course, is originally a little bit different. CAN is intended to be used in embedded networks in cars originally. And these days, we have CAN basically everywhere. We have CAN everywhere. In every system we use daily, like every elevator, maybe also these electric bikes from Bosch, Ubi, in medical equipment, everywhere we are having CAN these days. So it's in an embedded network. And Ethernet originally is more for IT infrastructure for connecting computers to transmit high-level data. And, of course, these days Ethernet is also going into some kind of embedded networks, as I just mentioned with the BMW. And all those different networks I mentioned, like LinenLocalInterconnect network, ByteFlightFlexure and so on, they have basically there some variations from CAN because of different requirements. So what protocols are used on CAN then when there is no standard? If you are looking into the cars in the in-vehicle network, there is no standard protocol still. Every car manufacturer using different proprietary protocols and you don't get any information on them except you are signing thousands of NDAs. It is a little bit different because we are talking about the diagnostics port of CAN, the so-called OBD2 port. There is an ISO standard on that and it is required by law that every car has this diagnostic port equipped. In buses and trucks, we are using a protocol from the Society of Automotive Engineers, which is the J1939, and maritime equipment. They have their own definition. It is called NMEA2000, but it is basically a variation of the J1939 protocol. In industrial networks, we are using CAN open, and also in some cars these days, we are going to use CAN open. What we can see data exchange is for almost all of these protocols is broadcast. We are just broadcasting our data to control the system, except for OBD2, there we are having direct access to inquire data directly. That said, are we having configuration in our system? No. Any car, any truck or whatsoever is not configurable. That means the manufacturer builds the system and it is deployed as it is. If they want to change something, they basically have to change the firmware. They can't configure anything. That's a little bit different in an industrial world where we are deploying stuff and configuring stuff later on. So what's about security again? Some car makers have started to implement security in their cars, like for automator correction, like for test control and so on. So there are some proprietary security deployed, but it's not that hard to crack. OBD2 basically has also not really a security. They have defined a simple access control to devices, so you have to write down a magic number or whatsoever, and if you know that magic number, you basically have full access to that device. In all those industries, we have no security these days. And as I said, the use case is in vehicle networks, we are controlling the car. On OBD2, we are doing diagnostics and all those other networks, like in trucks, maritime, industrial and so on, we are doing control and diagnostics. So the question, why we have those security problems in cars? That's just some numbers. The first Mercedes E-Class, and that's some kind of official numbers. The first Mercedes E-Class, Series W124, had only one CAN network and seven devices with about 100 messages. So that was basically a small group of engineers could handle that kind of network, and you can find bugs, whatever you... you can develop correctly basically. The next version was also somehow simple, but then in the 2000s, there was a Series W211 deployed, which had already five different CAN based networks with 52 electronic control units and over 4,000 messages. Now imagine that one engineer and a small group of engineer could handle such kind of networks, fully distributed. Everybody talks to each other and we have more than 50 different types of messages to handle. So nobody can oversee this and you can never simulate or you can never really test such systems. So obviously in those kinds of systems are bugs. And if some of you may remember, at the 2000s when the new Mercedes E-Class was deployed on the market, they had lots of electronic problems and that's the reason. They moved so hard forward in electronics and implementing electronics that they missed out bugs. And of course these are available today and they can be used for not-so-nice things. And just another image what I got from car manufacture. It was an estimate around from 2010. Originally we had only mechanics and cars. Right now we are talking about 30% of the functionality in a car is pure software. And that is going to increase. So we are having more and more software in cars. And how that happened, if you take a local regular network, then we see different areas in the car. We have a comfort network where we have connected all the lights, the turn indicators, stuff like that. We have another comfort area where we have connected the air conditioning, the seat position control, stuff like that. We have the trivetrain, which is responsible for our engine and for ABS stuff. And we have our multimedia network. And originally as you can see here, everything was connected on the very same network. So if I have access to any of those devices, especially in the multimedia interface, I have basically access to the complete bus. Sometimes ago the first car manufacturer started to separate those networks. So I have in a dashboard my central computer which provides some kind of a firewall. So that means if I have access to a network on the multimedia interface, I have not so easy access to network in the engine interface. Of course, those firewalls are not good. They have bugs. But they are getting better over time. And just to mention, the most current implementation with Ethernet in the BMW 7 series, what we have seen, we have now Ethernet. So the upper link is basically replaced with Ethernet links. And of course then for each of those different subsystems I have dedicated gateways and firewalls. So that means car hacking, getting more and more complex. But of course there are some car makes which making it not so difficult making it not so difficult for car hacking than others. So these systems what we have seen, what we are seeing right here with these different firewalls, that system what we can find currently and basically in German car makes. But if we are going to other car makes from US, from Italy, then we are still basically at this level. And now there is no wondering why we have those kind of problems. And just to reiterate, to get what happened in car hacking in the past, car hacking is done since some years. We have of course different law enforcement agencies undisclosed, I know some of them who are doing car hacking since years. So if you are, let's say, a hostage in a robbery, the car has some modifications on it. Assume that. We have in 2006 there was a paper, State of the Art Embedded Security and Vehicles. We had, at Safecom 2008, a paper on security to automotive can networks, technical samples and so on. The most important car hack I have seen, which was really a remote car hack, was at Youth Snakes at 2011, presented by the university in the US. It was called comprehensive experimental analysis of automotive attack services because they managed to attack a car via the GSM network. They just had an audio file called the car, played the audio file, reprogrammed by that, the firmware of the multimedia interface and had access to the car. Then, yeah, I said two years ago, almost two years ago, we had a small talk on scripting your car, which basically was displaying messages on your dashboard. Then we had, yeah, at Blackhead, Chris Wells and Charlie Miller presenting their paper, which basically was not that big of a topic because they had direct access to the car and did anything directly. We had just earlier this year this car hack of BMW Connected Drive and just last week, the same topic appeared to you connect to General Motors, to whatever, with all those different apps. And what we had, I think also last week just presented, I haven't seen that right now, but they had a talk on that. Again, Chris Miller and Charlie Wells said, they first, and I think that's much more important than their talk from last year, their presentation, their finding, is they done again a complete remote hack because some cars, as we may remember, in some cars, everything is still on the same care network. We have no firewalls and they managed to, yeah, to find some bugs in the multimedia interface and basically then had access to the full car. And that, I think that was just 30 minutes, so a small overview on car hacking, what have been done, and I think we will see a lot more over the next years, mainly by some obscure car manufacturers, but what I've learned is many car manufacturers these days, especially the European ones, the German ones, are aware of these problems and doing something because I'm working with them on some interesting things, like, yeah, we are converting, for example, taxis, police cars, emergency vehicles, stuff like that, and for all those cars which have a blue light on top, we have to manage to keep the engine running, which is something which is not intended by the people who are building originally the car, but we have to do it, we are required to do it, so we are doing some kind of car hacking inside of those different companies. And, yeah, and that's something what I would like to finish and if you have questions of topic, I can go in a little bit more details later on, yeah. Thank you very much. So I guess as we have many drivers here, you have something to think when you travel back home in the next days, and, yeah, maybe, as the speaker already said, you have some questions for him. There are microphones on that side and on that side, you just can go there, take the mic and ask a question and hope that the guys from the audio make sure that you are here. Yeah, any questions there? Will car manufacturers will they be implementing over-the-air updates for the software of the car to your left? There are different car makes which have currently over-the-air updates. It's basically Tesla. You know, when they just release the public note, we enhance our safety of the car by just deploying a remote update. As of now, I'm not aware that any other car make is doing remote updates. They are looking into it, but they all have those security implications. All the established car makes are aware of the security implications, so they don't want to do software update over-the-air. Some are looking into it, but have not decided on it how to do it. The only one I'm aware of is Tesla. Okay, thank you. There's a question on the other side. What the European key cards like in Renault and like Volvo have those in Euro? You don't have to have a key, but you have a key card and a start button. Is that an access point to the gateway, or do I have to get to the gateway? Or could I use the access card, the key card as an access point to hack the car? There is an additional firewall. These days, if you have those key cards, or it doesn't have to... In some cars you don't even have to put the key in a slot. You're just weird in your pocket. These keyless entry systems, basically. They're having established measures that those different ECUs are talking on a dedicated communication link to exchange data. But what we just learned is because all those comics, nobody really does develop anything by their own these days anymore. Everything is from Bosch, Delphi, Conti, whatever company. And it just happened that... Yeah, in Germany it's commonly known as the Volkswagen hack. The underlying company who provides the security of the key fob has a big problem in their implementation. And the problem is this technology is being used not only by Volkswagen, but also by Chrysler, by Volvo, by different. So there is a huge security implication currently going on when the paper for this hack basically will be released in September at the next use-next conference. Okay, thank you. Do you know how they handle priority in the Ethernet broad outreach? How they handle... priority-based communication in Canbus. But how they handle it in broad R. Ethernet is not priority-based. Yeah, that's part of the original design. You originally have to design your network. As an engineer you are starting your design. You are thinking about what is important, what is not so important. And then you are basically defining it all in the system. That's also different between, let's say, the IT infrastructure design versus an embedded design. In the embedded design, you basically know what you want. You know what the network will be, what the device is connected to the network will be. There is no arbitrary device is connected ever to the system, which is different in basically IT networks, where basically everybody is allowed to connect arbitrary devices to the network and then should be able to talk to the network and you're getting your IP address via DHCP. And that's not really part of the embedded network. That's also, if BMW, for example, when they use Ethernet in the car, that's not... You will not have TCP IP on that network. You will not have DHCP. That's an embedded design network. Okay. Thanks. So I guess all questions are answered. So once again, thank you all for the lecture here.


What's up ladies and gentlemen, Steph back here again for Freedom Central. And I'm with Alex, how are you doing Alex? I'm doing really well thanks. And what you enjoyed most about today so far? What I mostly love is the experience that people are getting. People really seem like they're into it and you really feel connected and that's what YouTube's great for. What's been your highlight today so far? I'm having fun with my friends. I want to enjoy this moment with my friends. You're going to sing Happy Birthday for your friends. So you guys have all come together I assume. And how long have you guys known each other? About an hour so that's what fun besties are all about folks. Meeting other creators and making friends. I've come to see Connor Frander and Alex Wasabi. Is it too much for you? Is the thought of Connor making your heart flutter? Yeah it does. And this is why... Connor! I really need to see you Connor. I'm a street team for Connor Frander so I'm really excited to meet him. That's awesome. We want to meet Connor and Alex. Connor and Alex, if you're watching this, I love you. I'm willing to see Connor Frander. Everybody wants to see Connor. I'm just waiting for them to come out. You're waiting to see Connor and Alex? Everybody's waiting to see Connor and Alex still. Nobody wants to see me. They don't even want to talk to me. This is terrible. This is terrible. Who are you here to see? Not Connor and Alex, me. Connor and Alex. So you're just here to look at Alex and Connor. It's very dreamy. So Connor and Alex, there's all these amazing ladies here that want to meet you. Where are you bro? Where are you? Locally, who's your favorite local YouTuber? Oh I like Mikey Bustos a lot. Some of his stuff is really good. He's pretty awesome. And I like Bogart also. They're really funny guys. Abra. Abra? Abra, same. Abra, all Abra fans. That's awesome and what did you think to Abra? We sang to him. That's awesome. Philharmonics and Connor Frander. Philharmonics will be awesome. Mikey Bustos, I just hugged him and told him that I love him so much. He just hugged him, stared at him, stroked his face a little bit. You gave him a gift, what did you give him? Somebody been a drinker. That's awesome. Who is your favorite local YouTuber? Lloyd Geddon. He's super funny and I like his YouTube content. Lloyd, Cathy Geddon. Lloyd, everybody loves Lloyd. Lloyd's awesome. Lloyd's the best. He's just like one of my spirit animals. He's a spirit animal. So you heard it here first folks. Lloyd is now a spirit animal. What did you tell by the big sign? Connor Frander. I've seen Tyler Ward. Tyler is so great. He's so handsome and cool. He's so cute and so tall. What did you ask Tyler? I asked Tyler to sing a song for me. This is the way Tyler did. He's mentally already. I asked him to greet me for my birthday. Did he sing you Happy Birthday? Oh, that's awesome. So you both had an amazing day so far. I think I'm excited to see everyone. Even me? Definitely. Oh, awesome. And what about you? Connor and Alex. More Connor and Alex fans. They're everywhere today. So who are you coming to see today? Connor Frander, AJ Robbie. That's awesome. Who is it you've come to see? I met Tiffany Albert and I was so star struck. I wasn't even able to talk properly. So I didn't ask her to sign. Have all you guys visited people as well? Who are you guys visiting? Tyler Ward. Tyler Ward. Oh, and what did you think? He's so cute. So this lovely lady here also has a YouTube channel. She produces vlogs. She produces let's play. She does all sorts of crazy stuff. Why don't you tell us about your YouTube channel?   I think I'm in love. And what is your YouTube channel, Miss? My YouTube channel is Marci Malos. I hope you guys check it out. What's your YouTube channel, sir? Juan Miguel Jeremillo. Vlog every weekend. Then Frank. And what's the most exciting thing you've vlogged so far? When I travel in Catanuanis. Oh, okay. That's awesome. And what about you, Miss? What's your channel? Catherine Tomau. And what sort of content is it you made? Filipino stuff. Filipino videos. Okay, cool. This little lady here has a very special friend. And she wants to plug her channel for you. My sister has a YouTube channel. Her name is Rhythm Oiko. R-H-Y-T-H-M-O-Y-C-O. Please visit her channel. And what sort of content does she make? Daily vlogs, makeup practices.  That's amazing. With one of our employees, this is Michelle. And she is a superstar. Hi, little family! She's been here all day. She's been meeting YouTubers and telling them about freedom. And this is in her free time. This is insane. This is what a model employee looks like. We love you, Michelle. Thank you. What have you seen while you've been here today? What have you enjoyed? Well, I've met a lot of local YouTubers. Have you got any messages for the rest of the staff that are still at home? Okay. Hey, guys. We'll give you a lot of opportunities. Okay, this is Michelle. She is awesome. And I will see you guys in the next clip.


I'm Watkins, community moderator at opensource.com with this week's top five. At number five we have what is your favorite open source java IDE from opensource.com editor Jason Baker. Jason says that developers have strong opinions about the tools they use and perhaps some of the strongest opinions come around integrated development environments. In the article you have an opportunity to vote for your own personal favorite. At number four, new writer Kaz Sato brings us a really interesting article about Google's open source machine learning library tensorflow. Reading this will show you how machine learning has the power to change how we work. At number three, Nadi Shalom has an interesting article about how edge computing is going to impact the next generation of IoT devices. In the article he explains why proximity matters and its implications for the future of cloud computing. At number two, Jimmy Shalom with a great article on what's the current state of Linux distros for kids. This is a great back to school article in which he shares the status of six popular distros and then invites readers to share their own. A lively discussion follows. Number one article this week on opensource.com is a programmers cleaning guide for messy sensor data. Any article, new writer Xavier Ho explains how to use pandas and python to clean up your data in this excellent step-by-step guide. That's it for this week. Thanks for watching and we'll see you next week.