السلام عليكم ورحمة الله وبركاته. ورحمة الله وبركاته. أحكام SOS. The show that discuss Islamic duties and practices for Muslims. By His Eminence, the Grand Ayatollah Said Sadik Shirazi. May Allah protect us from his life. I'm your host, Mohsin Shah. And joining me my co-host. The fantastic Sheikh Ali Ma'a. السلام عليكم شيخنا. السلام عليكم ورحمة الله. الحمد لله. Sheikh Nafiq. Remember we were discussing before doubts, valid doubts in Salah. We were discussing is it okay to abort the Salah or not. And we were discussing how it's performed. What I wanted to ask you was that some people are excessive doubters. And they are so particular about their Salah that they end up repeating themselves 4, 5, 6, 7, 8 times. Is this the correct methodology to use that? Yes, you should have 100% concentration. And 100% يقين that your Salah is 100% perfect. أعوض بالله السميع العليمنا الشيطان الرجيم. بسم الله الرحمن الرحمن الرحيم. الحمد لله رب العالمين. وصر الله على محمد واله الطيبين الطاهرين. الله مصر على محمد واله المحمد. It is forbidden for the one who is performing prayer and Salah. To repeat the Salah many times on the grounds of وصوصة or obsessive nefs. So it's haram to do such act. You cannot just keep repeating and repeating the Salah. Just because you're not sure if it's performed correctly with all the conditions. There are rules of doubts. If you follow them, if it's a invalidating doubt. يأبور ده صلاح. If it's a valid doubt, you follow the procedures. You cannot just do that. أبور ده صلاح and repeat again and so forth. Or even pray it fully and then pray again fully and again and so forth. You repeat. It's a waste of time. And Shaytan will be encouraging the one to do more. So he would deviate that mu'min from the right path. So we try to stick with these rules. And of course the وصوصة, the one who has this issue. They can just ignore it and follow the procedures and continue the Salah. So the best way is just to ignore it. And to overcome the وصوصة and the whisper of the Satan. أحسن الشيخنا. شيخنا, we had discussed beforehand that if you add or subtract anything from the Salah, you have to perform what is known as سجد تأسخ. So can you tell us when does that become obligatory? سجد تأسخ, they become obligatory and واجب in Salah. When somebody does these five acts in Salah. And number one, if one unintentionally speaks during the Salah. As we mentioned, if you say open the door or answer the phone, for example, mistakenly, unintentionally, then in this case, and it's not deliberate, be careful deliberately will make the Salah void and battle. But unintentionally, in this case, the Salah is correct. You just have to do two سجد تأسخ when you do the Salah. After ending the Salah, you do two سجد تأسخ. I've mentioned this previously how to do the سجد تأسخ. And then that's it, should recover this fault. So that's the first place or situation in which you have to do the سجد تأسخ. I think it's more common for people to say ouch or something like that in Salah. Exactly.  Exactly. So we move to the second one. And that is when you do تسليم in let's say the first ركعة. Suddenly you've performed something where it shouldn't have been. Exactly. You're performing something. And this act is not part of this stage. It is in the stage of the very last of the Salah. So تسليم is in the very last ركعة of the Salah. Third or second or fourth depends on which Salah you're praying. So in this case, when you finish, again, unintentionally, mistakenly you did تسليم on the first ركعة, let's say. In this case, you stand up, you continue the Salah, and then you do تسجده of سهو after the تسليم. Number three, if one forgets one of the two prostrations. So not both because they're both prostrations and سجود. They are ركون and key elements. If you forget them, the whole Salah is بعضل. But if you forget just one سجده. Yes. Or if you add an extra one so you don't throw it instead. Exactly. So if you do one سجده only, in this case, you go after the تسليم, you do سجده السهو, and that should cover this fault. Number four, if somebody forgets تشهد. Again, تسليم in the first place and then تشهد. Let's see you're sitting on the second ركعة. Which is called the resting position. So you did your two سجده.  You should have done what تشهد. Yes. In this case, if somebody forgets تشهد, they do also two سجده of سهو to recover this fault. And finally, if one doubts, so the check comes, after the second سجده in the fourth ركعة, after the second سجده in the fourth ركعة, asked whether he performed four or five ركعة. Oh wow. Again, in this case, you do سجده السهو to recover this fault. So these are the main five aspects in which you have to offer the سجده السهو. And overall, there's a rule in overall. Let's make it easier for the viewers that if somebody adds or deducts from the صلاح, mistakenly, unintentionally, not being delivered and so forth. In this case, if you add or subtract from the صلاح, mistakenly, then you have to do سجده السهو. That's important. But to remember, it is not if you add or subtract or ركن. For example, if you forget to do your ركو, or if you don't do two ركو. Exactly. That's excluded. That's exception. All the exception is the سجده. Exactly. If there's three سجده, or if there's one سجده, then you can't perform such this. Otherwise, no battle. Do it again. Exactly. Yes. The ركو must be performed. If not performed, then the سلاح's battle, whether you have done it deliberately or unintentionally, you forget to say تكبير تحرام الله أكبر. You forget. Yes. You show 100%. Not doubt. Yes. We said, if it's doubt, you just pass and carry on. Carry on. Carry on. Because you've moved to the next stage. But you showed 100% that you've got to say تكبير تكبير. Yes. You have to repeat the سلاح. I won't cover it. Exactly. Exactly. You start from the beginning. Mashallah. Shaykhna, what if I made a mistake in my سلاح? But I corrected it. If I repeated that mistake correctly. Do I need to perform the سلاح still? Or is it okay? No. Because you did it properly. It's fine. As I've mentioned, if you repeat that wrong eye you've recited, or let's say you forget to recite الحمد and you still haven't moved towards the ركوط, for example, even the سورة. Yes. You just have to recite the حمد again. Or if you've recited, let's say one of the تسبيحات by mistake, not in the grammatical way. You just repeat it. And if you say it correctly, there's no need to do the سجلية السهو or any other acts in which to recover this fault. Because you've already recovered the fault by repeating this verse or this word in this سلاح. That's fine. أحسن الشيخ. شيخ, what happens if I am in لسامن رقوط in my third رقا and I remember that I haven't performed تشهد or سجود. I missed one of the سجود in the previous رقا, in the second رقا. But I'm on my third رقا in my رقوط. What should I do there? سجلية السهو is enough? Well, one سجد and تشهد is واجب and سلاح must be performed. And because you forgot to perform them in the previous رقا you can't go back because you've passed the stages from one رقون to another رقون. You can't go back and do them. Just to make clear to the viewers it's not that I have doubt. I know that I have missed my تشهد. I know that I've missed one سجود and تشهد. I'm on my next رقا in the رقو. What do I do? Do I abort? Or do I carry on? In this case if you forgot the تشهد or the one سجد. Not true. One سجد. When you finish the سلاح and you say السلام عليكم و رحمة الله و بركاته after the تسليم you make the intention of the forgotten تشهد. Let's say. So why are you sitting without moving and preserving the posture of the سلاح as it is. So you do the سلام and then you make the intention of the forgotten تشهد. Okay. So as if it's قضا تشهد. Exactly. قضا تشهد. Okay, just make the knee in your heart. And then you recite تشهد. And that's it. That's it. That's it. Or the سجود. Okay. You finish the تسليم of the سلاح you go to one سجود Yes. And you do قضا of سجد. Yes. And that's it. You've done and you've recovered this fault. But also the say it says that you should also perform two prostration of سجد السهو. Okay. Again. Because what you have deducted from the سلاح. Yes. You took off one or two acts which is the شهد and one سجد. Yes. So in this case you also do afterwards سجد السهو. And you pray these two سجد When should one perform سجد السهو? As in I've done ذهر. I'm I'm very eager to pray أصر. If my سجد السهو is for the ذهر prayer. Can I pray أصر and then the سجد so for the ذهر prayer after or should I pray directly after ذهر prayer. The two سجد of سهو they must be done and performed after the or deducted something from the صلاة. So you must do it in order to recover this fault. But if you forget whenever you remember you must do the two سجد whenever you remember so it's important that you don't neglect and ignore this two سجد very important to recover this fault. The addition or subtraction of from the صلاة. Thank you very much. And thank you for coming there and we ask you to remember us in your دعاز and please remember the channel in your دعاز until next time. السلام عليكم ورحمة الله وبركاته.


Hello everyone, can you guys hear me good? All right Okay, so I guess we can get started Let's start off maybe with a who am I why I'm here speaking to you guys about duck to be right? So I did my ptsz in database architectures At CWI is anyone here from the Netherlands? Oh So I'm gonna butcher your language a little bit. I'm sorry So CWI is the centrum viscude informatica Which is the center of mathematics and computer science in Amsterdam? And it's actually the place where duck debut was born. So that debut was born in the database architectures group Also CWI is where python is born in case you didn't know so there you go Also the first point of internets in the whole Europe. So it's quite a strong research institute in Europe So I did my ptsz there in the index structures and while doing my ptsz I was already working at duck to be so you can see there on the GitHub history it was basically the co-creators of duck to be and me On the first July to August of 2018 so long long ago. So today. I'm a software developer duck to be labs Which is a company that Maintains and Continuous development in duck to be and I did all kinds of stuff. So of course I did my ptsz in indexes So first thing I did in duck debut was an index. I did zone maps. I did arrow adbc Substrate integration. Maybe you guys heard some of these words earlier today on other presentations What the main reason I'm here is because I did the big chunk of the python API. I'm not a python guy per se I'm a C++ guy, but I did my very best And I'll show a little bit of that to you guys today worked on the CSV reader and tons more of other stuff So a little bit of the outline of the talk today I'm gonna go quickly over motivations are really about database systems for data science and data analytics Talk about the alternatives. So classic server clients and data frame solutions And then of course gonna talk about in process database management system Specifically duck to be and what makes duck to be so special. So what were the design decisions there that make it Different from all these other solutions, of course, there's a python conference. So I'll talk about duck to be in the python lands our integrations what's our users are the different APIs implements and python UDFs I'm gonna do a little demo and then finish off the talk alright motivation So this is a classic data science workflow So usually data science what you do is you start off by exploring your data You have a question in minds and then maybe you zoom in on a piece of data to try to investigate if your question or hypothesis is correct You explore it you model it. Maybe it's like suddenly. Okay, this is wrong I'm gonna analyze something else entirely difference and you kind of keep repeating this process all the time So if you think about the workflow is simply that's asking interesting question get the data explore the data model The data visualize the data repeats If we think about the libraries that are part of this workflow We can think of asking an interesting question exploring the data. These are basically queries, right? We're actually trying to get pieces of our data and then model it So for example tensorflow or pytorch and visualize it with potli or metlop metplotlib And the data comes in all shapes and forms, of course Nowadays you have JSON files CSV files parquet files you have binaries from other database systems But the interesting thing here is that in two of the two important pieces of this workflow. We need a database engine And this database engine as we've seen previously must scan all these different file formats, right? So File comes in all shapes and forms and most integrative ecosystem too. So if you think about these Machine learning libraries if you think about the plot libraries, they're frequently well available in Python But you need to be able to get your data in and out To these tools and it must be efficient In executing analytical queries data science that analysis these are analytical queries And you must ensure that they go beyond memory execution There are nothing more frustrating for example if you're running Your query on your computer and just because your data doesn't fit in memory. Bam. The whole thing blows up, right? It must also handle complex query optimization and when I mean by complex query optimization It's not only future pushdown or projection pushdown, but also sub query flattening for example And one thing we also notice is that is Like there was a talk earlier on talking about a relation API in seco and how they differ and the benefits of each What we notice is that people usually use both of them in different parts where they fit most So these database engines should be able to support these two things and When we start to see about the alternatives of how you could do data science you can think of of course Classic server database systems relational database systems like postgres SQL server Oracle Years of database research embedded into them like I'm talking about 40 50 years So they have a full-on query optimizer. They have a buffer manager So they can do data that does not fit in memory. They have their own storage So they can apply compression and have everything in one file. They have a state-of-the-art Execution engine they support SQL, but I have a question for you guys Has anyone ever managed to set a postgres instance for example in less than five minutes to read a parquet file? two people three people More or less ten minutes, maybe it's tough. It's difficult to set up So it requires upfront schema creation. You need to know exactly what your data looks like It doesn't have any integration from the lyrical ecosystem So if you want to then transfer your data to I don't know tensorflow for example You're gonna have to write something that queries this and that transforms the data there And the way this works when you think about Python as the figure Do I have my mouse here? No, it's the figure down there like you have your relation database system You have your Python lyrical tool, but your whole data needs to go through the database connector So basically you copy and transfer in this data. This becomes a huge bottleneck. So that's a no-no The other solution is data frame libraries They're pretty cool. I mean everyone here uses like pandas for example, right and integrates with these ecosystems very well They use like NumPy or PyR underneath Very easy to use with pandas. You can read the CSV file in more line You don't have to set up a schema all the magic happens for you They have relation API fast data transfer because you're running the same Python process So usually they integrate so well of these other libraries because they also talk NumPy or PyR that you don't really need to do any copying And as I said, like with the CSV files or parquet or whatever These they have so many integrated scanners for all these file formats with the schema detection With automatic schema detection Well, the problem of data frame libraries is that they are not such great analytical Engines so usually they don't support SQL or support just a small subset of SQL Usually they have no query optimization or only simple query optimization. So no sub query flooding for example It's frequent that there's no beyond-memory execution So if anyone here again use pandas before, you know if it goes over your memory The whole thing burns your Python process dies and that's it. There's no storage So basically you're gonna be still handling whatever CSV parquet files a bunch of them bunch of hard-coded path becomes super cumbersome In the case of pandas, for example, there's not zero parallelism like everything is single threaded So it doesn't matter if you have a shiny new Mac book. So you're just gonna be one thread So we decided to Okay, we kind of want to do something like nice as data frames like easy to use Pleasants people enjoy it. But with everything we know from academia every all the cool stuff to make an analytical Query engines good, but where can we draw inspiration to something? That's like a database system, but kind of similar to data frames and that was SQLite So SQLite is an embedded database system. So it runs in process There's no external server management. So you don't have to do any of the setup that a postgres has it has basically bindings for every language The storage of the database is one single file. So it's easy to transfer Public domain super easy to use. It's actually secretly secretly the most used rdbms in the planets It basically runs on every cell phone every browser even airplanes, so It's great. The only problem is it's built for transactions and not for analytics So that's kind of like where duck to be the idea was from so we won't do something for data science That works very well of these analytical tools like Python in our so very well integrated zero copy That works with data visualization that's small and can be putting any sensor you once for example And see a very strong execution engine for behind analytics Doing resource sharing because of course you're running the process So you need to be able to communicate with the other processes and again with the fast data transfer And that's of course the beautiful table where we have like data frames client servers SQLite They're all lacking something duck to be has it all And I'm gonna show you guys a little like I'm gonna give you guys a crash course and database systems in a bit All right, duck to be so as said We wanted something that was easy to install simple to use to install duck to be in python pip stall No big secrets. It's embedded. So there's no server management. It runs within the Python application Has fast analytical processing has this fast transfer supports full SQL so our our parser actually was The postgres parser is a single file format is free and open source under the MIT license Which I think is the most permissive license out there. We currently in pre-release So our version now is 0.8 point one You can of course check the website for documentation and more details about this So let's do a quick crash course on database systems. I'm gonna go each of these topics of design And try to explain like what makes duck to be different from for example SQLite and pandas So when you think about data layouts, you basically have two ways that you can start your data You can either start your data from your table Contiguously memory per row or per column. So SQLite has continuously per row Which means that if you think about the memory, you're gonna have first the first row Then the second row then the third row so and so forth That's pretty nice because individual rows can be fetched very cheaply So that's very nice for a transaction databases and for example And it's particularly nice when you don't have a lot of memory because that means you only need like one memory one row in memory per time but The problem is if you have a white table and you're not actually using all the columns You're still gonna have to fetch all the columns. So for example for not only interested in the price of a product in our example here But not the stores in which the product is sold that still means you're gonna read the whole table The other Option which is a column star. So basically any analytical database will be a column storage these days duck to be or pandas We can actually fetch these columns individually because now the columns are stored sequentially in memory And then this brings immense savings On the disk IO memory bandwidth when you only accessing a few columns So again, if we have the same query very only interested in the price of a product We would have the products and here's Not the dates and stores Yeah, so basically we have products consumer and price So then this reduces already the number of columns we would be reading from here So if we get like a bit to the numbers, let's say we have a 1 terabyte stable with 100 columns We have a query that just requires five columns of this table in the row stores on the SQLites postgres You're basically gonna read this whole terabytes from this which at 100 megabytes per second It's about three hours a very in the column store That means that you only actually need to read these five columns, which is 50 gigabytes that reduces the time for eight minutes the other nice thing of actually having a color database is that You actually have the values of the columns again sequentially memory is that the columns usually have similar values So for example dates are usually increasing and that means you have more opportunities to apply compression So here in this table, I have that to be from version 0.2.8 So that's July of 21 there was no compression and then we implemented a bunch of stuff so implemented constant compression implemented repetition implemented bitpacking implemented compression for strings for floating point numbers So in about a year and a half we managed to reduce for example line item Which is a classic table from a database benchmark Up to five times and the taxi data sets pretty classical for data science up to three times So exactly by taking this leverage of the similar data being stored So if we go back to our example That we only required the five columns from the table which were 50 gigabytes and took us eight minutes now by applying compression So about like five times of savings, of course, this depends on your data types And all this time can already be reduced to a minute 40 The other thing that I can talk about of course the execution engine So SQLite uses what we call a top of the time processing So it process one row at a time through the query plan Pundas uses a call at a time processing which means the process entire columns per time and duck DB uses this technique That was actually created at CWI Called vectorized processing which process batches of the time so not really rows not really columns But small pieces of your table So if you think about the top of the time again It's from optimized from when you didn't have a lot of memory In your computer and that's because throughout your query plan. You only really need to have one top at a time However, because you always passing this one row per operator You always clean the caches of your CPU. So it creates a huge CPU overheads So basically when we're executing a query we go row by row query process result query process results and so on and so forth On pandas you because it's in call at a time or I have better CPU at a station. So for example, you can do seems it single structure multiple data But the problem is that you have to materialize the whole column into memory So if you don't have a lot of memory, you're gonna go get into trouble because these intermediates of course can be gigabytes each So again the examples that would process one column the second column and then get to the results That to be again is the vectorized processing is optimized for CPU cache locality It still allows for CMD for pipelining and the whole idea is that you have this Intermediate ideally fitting in L1 cache So for example, you would have like the first chunk main process getting the result the second chunk main process getting the results I'm not so sure how familiar guys are with CPU modern CPU architecture But basically you have the CPU core and then you have these Caches up to the main memory and the difference of them is that the cache is closer to the core There is smaller but have a very fast access and further from the core They are bigger, but they have a higher latency So by fitting your data in L1, which is the size of these batches inducted be you basically paying your latency of One nanosecond it's pretty fast, but if you think about your data from pandas I was not gonna we're talking about gigabytes of data, right? So that's not gonna be fits in L1 not gonna fits in L2 not gonna fits in L3 It's gonna end up in main memory So then suddenly for every time you access in some piece there You're paying this huge difference in latency and this that's where this bottleneck in execution engine comes from My computer is not yeah cool So the other thing I talked about of course it was a query optimization so Duck to be this all sorts of stuff that does expression rewriting the does join ordering Subsequent flattening filtering projection pushdown and here I have an example of how this is done automatically in duck to be but manually in pandas Right, so basically I have a table here with five columns ABCDE and I'm getting the minimum of a Applying a filter in a and groupie by by be rights So what we can see here in the duck to be planned for the more to the right is That in this scan of the table we are already pushing down a and b in the projection So basically like okay this table has five columns, but we actually only interesting this to so just go With these two up to the plan and then if we go to pandas where for example, we start off by filtering our data frame So getting The values from our data frame where column a is bigger than zero and then doing the group buying the aggregation That means on this filter data frame. You're not pushing down any projection.  They need to be manually done Duck to be again has parallelism so has parallel versions of most of its operators Scanners aggregations joins and scanners. They can also be insertion order Preserves so basically it guarantees that the data will be output in the same order was inserted so here I have an example of a an aggregation of TPC 8 squared classical benchmark for database systems on a scale factor 10 So basically what we can see from the charts is that the more Fred's you're putting there is actually going down quite nicely, which means that parallelism is working very well It also has the beyond-memory execution So it's not only because your data doesn't fit some memory that everything should burn down to the ground, right? So we kind of have this never give up never surrender mentality doesn't matter if it's gonna take a little longer We're gonna execute a query at least that's a go So we want to support this also if graceful degradation, right? It's not oh oops Doesn't fit senior memory for one megabyte. Now it takes way longer. No The the last it fits of course the more impacts that we'll have but it's not gonna be a huge spike so here for example, I have a hash join on the X axis I have a memory limits in gigabytes the data itself fits in 10 gigabytes and then we can see that's Okay, the time is going up, but it's not drastically going up the last memory we have So Python integrations Well, we actually integrates with the Python ecosystem. I would say quite well The thing that we ourselves did here very strongly was to integrate of this data formats So when you think about numpy pandas arrow pullers and pytorch, we really try to have Zero copy integration with them, which means that we can transform for example to Pandas and read pandas data frames that I'll copy any data TensorFlow that's not really true, but we still integrate of TensorFlow and then All these other libraries for example there are the IBIS projects data frame API We're actually the default execution engine of IBIS as well Yeah, there's lots more for reference a bit of usage So this is the amount of downloads that DB had on the last month So that's about 1.3 thousand that is only for the Python clients, which I think it's still our biggest clients Again, we have clients for many different languages But that already gives a feeling that is a project that's maturing quite well. It has been quite used So we have over 11,000 stars over 200 contributors And it's used by over 3,000 projects on github APIs we do support the classic Python DB API so where you create connections You create cursors you execute your queries your fetch results so and so forth We have a relational API that's more inspired by a pandas so You're gonna basically be able to for in this example here You have a connection and then you can create a relation that points out to a table in the DB And then you can start to chain operators, right? So you have okay this table relation I want to apply a filter I want to apply a projection so and so forth So it has a look and feel similar to data frames We also have the spark API. So the idea of the spark API is that it's gonna be one to one With the extra spark API It's still a work in progress But yeah, if anyone wants to contribute to that you guys are also very welcome Last but not least Python UDFs This might be too small for the people in the back Unfortunately, but the idea here is that you can actually have Python code that can be executed directly for SQL So in this example here, I'm basically creating a World cup titles So it's just a dictionary of name of a country and how many times that country want to work up Then I create a function called work ups It basically just do a look up on the dictionary So very simple Python function, but I can register that function in duck DB with a name And I just have to give like what's its inputs and what's its outputs in this case is just a var char String and then it's gonna output an integer and then I kind of create a table with countries So for example, Brazil, Germany, Italy, Spain, Netherlands And I can apply directly that Python function via SQL So of course this example is quite simple, but you guys can imagine about doing Machine learning via Python UDFs And then after appliance, of course, you have the results of Brazil with five word cups Not unless with none. Yes, but maybe in two years Now let's go for the demo All right Is this good enough for the people in the back? No, yes, no bigger like this That's good. Cool. All right. So, uh, I start this example here by installing So this is a colab And duck DB and pollers, for example, they already shipped with colab So I actually uninstall them and install them again just to show you The sizes of these libraries I download then free data sets. So it's basically the the cab data sets So it's the cab rides from New York from January of 2016 I get the weather in the CSV file for that month and I get a JSON So that's basically it. So here what I want to show first Is that duck DB has about 15.9 megabytes. So it's quite a small library When we look at spoilers is 19.1. It's a little bit bigger Nothing too crucial. It's too crazy. But when we look at, uh, spark, that's 310 megabytes. So that's like 20 times bigger. So I expect 20 times better performance. I think that makes sense, right? Um So when we go here, uh, for example, to just execute a SQL query in duck DB, you can import duck DB You can just do a duck DB SQL with the SQL you want to execute as a show and you already have your results Again, duck DB can read from all these different file formats, right? So for example, we have a from CSV auto function that we just passed the CSV path for the file automatically detects all the types column names and reads the CSV file We can do the same for parquet files. So duck DB has a from parquet function. You pass a parquet path does the same thing Automatically, it's completely able to read that parquet file And you have the same thing for json. So when you pass a json path Again, if we read json function, it can just read json files So it's very well integrated with all these different file formats We can also read postgres database files and sqlites database files directly So We can also create duck DB tables from these files. So in our example here We're creating a database from duck DB called rdb dot db And we're basically creating the table csv json and parquet Selecting all the data from each of these paths And the parquet file specifically is quite sizable.  So I can't complain Yeah, it's done And then the nice thing of this is that we can connect against this database that we now just stores And creates relations From this table. So we can create for example csv relation that points to the table csv that we created here, right? And then we can get that relation and use to csv. So we can now output csv files as well We can do the same thing with the parquet. We can go and point to the parquet table We just created and you can use the to parquet function and then we can also put a parquet file So we can also input and output these data formats Uh, so let's go for a very quick performance comparison between pandas duck db and pyspark So here i'm just importing the libraries Here i'm just i just want to show like how big the the new york city datasets is so it's basically A table with multiple columns of different formats integer 64 times temp doubles and whatnot and has Three three ten million now almost 11 million rows So to benchmark this of course, we're going to have some kind of time function So this is basically running the same thing five times and getting the meantime And we're going to do everything from data frames So i'm not going to give duck db the advantage of having the data in its own formats But we're actually going to go through pandas data frame. So we created their frame by reading the trip data parquet it's reading it All right So then the core you're going to execute is actually rather simple. We just want to the passenger counts the average supermount For distance for short distance. So there are under five miles grouped by the passenger counts So basically we want to know how much money our passengers are Cap drivers getting From tips with grouped by the number of passengers So we can run this in duck db And then this takes about 0.29 seconds and Because duck db can also again outputs back to a data frame and that's where we're turning here as well We're we're consuming upon this data frame and returning upon this data frame We can also use like the nice plots function from pandas and then we can see here Or maybe this is too big The number of tips per passenger The interesting thing here is that um, zero passengers is actually getting quite a sizable tip amounts. Not sure what's going on there But it's new york, you know, I don't know Then we can run the same thing with pandas. Uh, so again pandas is just reading its own data frame executing Uh, the same query but using the pandas api And it's going to output the same plots. So now it took 1.7 seconds Quite more than duck db and again, remember this is a machine that's not very powerful, right? It's a colab machine If you run this on your macbook, this difference will be more drastic And then we have basically the same plots and now we're going to run it with spark So actually with spark, uh, I tried to run it through the data frame, but it actually crashed my python process So I had to allow Spark to be able to execute it By creating its own data frame through a perk file, otherwise I couldn't bench mark it because it was crashing my colab machine Uh, so this is running Yeah You guys want to talk about something? Yes Yeah, um, so of course, I would say that queries like this are not exactly data manipulation, right? Like you're actually applying There's a proper query, but it's a simple query for the For the the purpose of the example, but you can use it basically whatever you want So you can use it We really designed it with the local machines in mind So our initial goal is we want users to be able to get the max of their laptops But you can totally put this on the server And we actually have a sister company called motto duck that's actually doing duct db for the clouds But starting from your laptop. So the premise is a bit different You only grow when you cannot feed things on your laptop anymore and then you start paying the the cloud providers um So it's spark finished, uh, so it's 3.5 seconds Uh, yeah, so I guess all that size, uh, didn't really help them all the time More yeah more megabytes more time apparently, uh Sorry All right, so quick summary Duck db is an in-process database system. We really focus on this fast data transfer None of this dedicated server has so all the goodies from analytical dbms So really take imparting the users with all the cool stuff The academy has been doing for the past 50 years is really designed for analytical queries So think about data analysis data science again, it's open source Other MIT license if anyone wants to take it fork it create another company make money out of it feel free You can't do that. It's completely free to use Has binding for many languages. So here show python boy. I'll have our java.js go If there's a language out there, we probably have a binding to it Very tightly integrated of the analytical ecosystem. So from the example I showed you We can even read data frames and be faster than pandas playing their own game kind of And has full cql supports Let's but not least I actually brought some I only had this here So I wouldn't forget but I have some keychains and Stickers guys, please don't let me go home with this.  Thank you Thanks Pedro for a good session and Probably Making ducks out of our databases if we can say that so yeah We have a few minutes for quick q&a's and for that you'd have to come to the microphones that are here And yeah, thanks Hi, yeah, thanks for the duck TV. We love it We are using it with lambdas. So we have so many lambdas. We simply the problem into many pieces So our quants are relying on so many group by operations And you know, lambda has a limit a ws lambda and in memory wise and temp memory wise And I think group by is Depending on many temporary storage in in duck db. Do you Can you suggest anything to overcome with the memory issues when we are having grouped by operations? Um, so I think recently on the last version there was more work done in the So so if memory issues you mean it's crashing because there's not enough memory. It's just okay Yeah, so I think on the last version. We had more work on out of core Group buys. I'm not sure exactly which version you're currently using If I'm not wrong 0.1 We pinned that If I'm not at 0.1, it's 0.61 0.61. Yeah, that's that's already quite old. I would say so there had already been a Seven seven one eight eight one like four releases after that. So I would suggest you try the the latest version. Okay. Thank you. Cheers. Thank you Other thanks a much for the great talk So we usually deal with the situation where we have effectively like a dag of expressions And it's not like a kind of a root node of the first expression And then we have like drive of expressions from that you can express that that multiple sequel operations, for example Do you think it would be sensible to use duck to be With multiple sequel operations effectively to create like a tree of expressions Would that be like a lazily evaluated somehow or So even if you So I'm not exactly sure how your expression or implemented that case I'm using something like a data frame or right or because even if you use the duck to be relation api The relation api it doesn't really execute the query when you chain operators. So it Creates a query plan That's actually only optimized and executed when you reach certain comments So for example, and you try to fetch results. So all right, so now is the point that we can actually get the query and Really go through the optimizer which Yeah, we will do unchain or something like this and Get a good result for you. So you should totally be able to do that quick follow-up So then it would probably like still already work for our use case if we just like try to use it I think so and then if the data changes on this say you would need to Recompute and the you would you would effectively have a new query plan You would have the same if your data changes, right? Yeah, so you say a part of the data changes Yeah In a nf file on disk Say in a parquet file, for example, would that be a fast operation or The data changes in a parquet file. You have to reread the parquet file. Yeah. Yeah The duck to be itself it supports updates. So we do have mvcc implemented Kind of like an mvcc for analytics. So if you're using the duck to be formats, uh, that would be Quite fast. I would say but if you're Doing updates, uh, somewhere else and then, uh, also putting a new parquet file, you have to reread that No way around that. No, perfect. It's really good. Thanks. Cheers Hi, thanks for the talk. Uh, yeah, I was just wondering if you could explain a bit the relation between substrate and wdb Uh, it's between substrate and duck to be yeah, uh, yeah, so We actually have support for substrates, but we don't use substrate internally in any way There are some other database engines like vellux, for example, that I think Uses substrates their actual query plan What we do is we have an extension That allows users to read from substrates and to Output substrates But that's not really used internally in any way. I know there are some users and clients that use it and What I can tell you about the current status is that we can roundtrip most of the tpc8 squares So there's still some problems with, um Correlated subcourts, for example And and we can work some queries as well with ibis, for example, but it's still very much a work in progress All right, thanks Pedro, thanks for your talk and thanks for duck to be which looks like a very promising Thing out here. I've been playing with that and having very good results. So the question would be We're at release zero eight one or something. What would the duck to be team call? One dot zero release. What would be the conditions assuming that Zero dot something is not stable and one would be stable and that's my assumption Yeah, so I would say that it's not that execution engine is not stable or that like I think it's quite well tested by now What we would call the one point zero is when we have a consolidated storage formats To the point that we're always guaranteed that we're going to be able to read Database files from previous versions. So because our storage formats to changing quite frequently Because of new structures, we ended up adding we didn't want to have this hassle of having to handle it So currently like if you change to let's say zero point nine, you basically need to do an export and an import Of your whole database file And there's an estimate for that calendar wise. Yeah in the next 24 months The estimate was last year.  Thanks Hey, so love the talk and the energy My question would be about first of all the name because it sounds like the focus is mainly on the compute Not the database part, but the duck part is great. So that one and Does duck db actually provides something or promises About fault tolerance because you said that you you can spin up on the server and use it in production in pipelines, for example but what happens if there's a faulty data point in the Stream of data that is coming So, uh, how does it handle that? Yeah, so for the first question about the duck, uh, yeah, I mean the reason it's called duck db is because you know Ducks are quite versatile. They can fly walk swim. I'm joking guys. This is a corporate answer The real reason is because one of the co-founders The guy lives on a boat So because of that, he didn't really want to have like a dog or a cat. I guess they're not great swimmers So he thought that a duck could be a perfect pet So he acquired a pet Or he adopted a duck while the duck was still growing and when the duck of course became adults I went to to live its own life. But um, he grew very fond of his duck and He he wanted to name his system duck db and that's a real story About the fault tolerance So we do have for example checksums in our storage to guarantee that the storage is not corrupted But there are definitely errors that could still happen that Could potentially corrupt your data Um But we do have some uh, some more basic checks on it Even in the middle of the compute for example, if I have one million rows and it fails on the 900,000 one The do I need to do it all over again? Yeah Yeah, basically those are most likely froze some kind of exception Um, and then you have to re-execute it Okay, I mean we I guess you can't have some kind of caching mechanism or all that but we currently don't Cool. Cool. Thanks Thank you Pedro. Thank you everyone joining us in the room and remotely and that'll be the end of session Have a nice evening here Bye


Hello and welcome to the session. Let's work out the following problem. It says the resultant of two light parallel forces P and Q acting at A and V, 8 centimeter apart is 40 Newton. If the resultant passes through C where AC is 3 centimeter, find the magnitude of the forces. So let's now move on to the solution. We are given two light parallel forces and their magnitude acting at C and magnitude is 42 Newton and the forces P and Q are 8 centimeter apart. Now we have to find the magnitude of the forces P and Q and since R is the resultant of the forces P and Q. So we have P plus Q is equal to R which is of 40 Newton right and also since this is a system of light parallel forces. So P upon BC is equal to Q upon AC is 3 centimeter and AB is 8 centimeter. Therefore, BC is 5 centimeter. Let's name this as one. So from one we have P into AC is equal to Q into BC. Now AC is 3 centimeter. So P into 3 is equal to Q into 5. So from this we have P is equal to 5 Q by 3. Now we know that P plus Q is 40. So we have P is 5 Q by 3 plus Q is equal to 40. Now taking LCM and simplifying we have 5 Q plus 3 Q upon 3 is equal to 40. Now 8 Q is equal to 120. So this implies Q is equal to 120 by 8. So this implies Q is equal to 15 Newton that is magnitude of the force Q is 15 Newton. Now we have P is equal to 5 by 3 Q 5 by 3 into 15. So this is equal to 25 Newton. So we have magnitude of force P is 25 Newton and magnitude of force Q is 15 Newton. So this completes the question and the session. Bye for now. Take care. Have a good day.


Yes and we are back with some more wine in the morning as promised and yes it's time for enterprise of first item of the day on entrepreneurship Tuesday and this one is some sort of social enterprise this is somebody who is giving back he's not in it to make the money and is from quench foundation and he goes by the name Mahon Jorogic Haribu San. That's Santa Santa. Alright, camera is number four right there just look them straight into the eyes and introduce yourself how you would like. Thank you so much first and foremost my name is Mahon Jorogic from quench foundation Kenya charity and mentorship and profit organization based in Kenya but working with the East Africa region. So we are happy to be here. That's us. Alright when he says we are happy to be here he has a team with him don't get it twisted but yes you're here to represent quench foundation how old is quench? Quench foundation we've existed for a number of years but we came together now as quench foundation about a year or so ago. Alright so when you say we how many are you? For now we we have a membership of about more than 50 members myself being the founder we have a group of directors whom we sit on the board of management and of course we have many other members who are partners in the organization. Alright it's quite an interesting name right there that you have quench. I quickly think of water or sprite yeah what is it for you? Okay quench let me put it this way let's think of it as an analogy when someone is thirsty you need to give them water the same same case we saw that there existed some some gaps in the industry in the market in the society and these gaps something needed to be done and that's why we came in and we started helping where we could. Alright so tell me some need. You saw some need and you came into like a straight business man but the only difference is that this is giving back this is not for profit. Alright so tell me some of these gaps that you saw in the in the Kenyan society but the gaps that needed to be filled what was the lack in the disconnect? Well in the Kenyan society there are so many gaps and of course as quench foundation we believe we don't give because we have we give because we can and so for instance in different communities different schools so many young girls are missing school because of lack of sanitary towels so that was one of the needs in the different institutions nursing homes children's homes they needed clothes they needed the same sanitary towels food stuffs shoes and so forth so on so that's why we came in and we started helping where we could. Alright so girls I've seen girls in the list I've seen students at large in a list of not the same citizens are they population that you work with as well? Well you know quench foundation being a charity and mentorship organization I've mentioned that we also go to nursing homes different nursing homes homes for the elderly people and we give them maybe something in accordance to their requirements for instance we don't just go and give first we visit them we know what their needs are then we are able to give them something which will be beneficial to them maybe in a certain children's home nursing home what they need are mattresses that's what we are able to give but just giving for the sake of giving we give something which we are going to impact them so you figure out the need first yes and then you fill the need yes alright so are you Christian yes you Christian so I'd like to take you to the Bible a little bit and I've asked that says you teach a man to fish instead of giving them fish yes alright so when you teach them to fish you've saved them the rest of their lives when you give them fish you've just sorted out a meal or one day all right so I like to bring you back to quench foundation is there a way that you teaching people to fish as well apart from just giving them fish yes actually that's why quench foundation is a bit it's a distinguished factor in the market right now because what we are doing is that we've incorporated charity with mentorship for instance in one of the objectives is to support upcoming talents we don't just maybe go and pay a study for you what we do is we work with you we connect you with people who are going to make you grow for instance maybe someone is a musician he or she is greatly talented but you know just going and paying the studio does not solve anything you need someone who will hold your hand and work with you for this because it's a whole journey yes so quench foundation is just give we don't just give and go we are here to stay with you and work with you for the rest of the journey until you are independent as as people say sounds like a lot of work right there and who's involved in all these things apart from yourself yes we have a group of people we have a chairman in quench foundation his name is Peter Moema a guy who is doing an amazing work and youthful like yourself yes yes we quench foundation we could say it's right to say that is a magnanimous platform magnanimous all right for for young people you remind me of a friend of mine called ks he's such using such terms all right so it's mentioned mentorship and helping when necessary also right i'd like to know what really drove you into getting into into non-profit work well you know we have so many people who inspire us to do these amazing amazing things but people who maybe have inspired us to do what we do are people like Bill Gates and you know people for instance in Kenya they think of this kind of foundation when they want to leave a legacy maybe at their old age but as i've said we don't give because we have we give because we come so we kept me and we started doing what we do and you know you went to the bible you know proverbs 19 17 it says whoever gives to the poor means to the lord and in time the lord will give him amen yeah all right so whoever gives to the poor lands to the lord and in due time the lord will repay him back yeah we'll take we'll leave it at that for now at the moment i'd like to drive you guys to our social media platforms that is twitter and facebook and we have a question for you how is it working from home how are you working from home and now that the president said that we should avoid social gatherings and we should also do the most trying to protect ourselves from the coronavirus and protect our loved ones and our neighbors as well and i see you guys have jumped on the bandwagon uh for sure and uh the comments keep coming so keep them coming and don't forget to tell us where you're watching us from so we can give you a shout out as well so thank you very much for watching thank you very much for telling us where you're watching us from from lele i'm working perfectly the only problem is payment won't be able to pay myself because my work is here cooking eating from a superior and watching white for thank you very much for that the money is gonna come if you have faith all right uh kate marshall rush rush for the summer from yungosu getai become mini village in uh engineer electrical kate uh marshall rafter rush for the white in the morning always i love you so much i like that bikanami village that was very detailed and that's how we love our comments thank you very much uh kate marshall rafod rush for samson fondo and i say my uh hashtag white for sabaki at the river watching live after night shift job as security guard wondering how and who will pay you if you work for yourself and lessons online business all right i see you i hear you cry for that but i didn't think you probably said but good morning to he coronavirus in a to let us see the sun as well wanna be wanna be a share on our phones the way to to umba was ilale but what's so many umbani molla at wangale we'll end up we'll hold it at that and thank you very much to timothy kipro and i took my word of advice to our students and i say so many because you're gonna resume school and and i'll be our kenya and we hope this is not going to affect us uh physically uh biologically and economically back to you uh mister uh so uh you told me uh you were telling me more about uh your work and uh how it's affecting the lives of the kenyan youth uh to the senior citizens right there and how you got into it so what i'd like to know what are some of your next projects well on the 28th of march uh this uh this month we have a project dubbed the essence 2020 uh the core value of the core meaning of giving that's why we've dubbed it the essence we are going at a certain children's home in limuru we were there we call it uh reke we would understand yes i reckon yes so we went there we we we surveyed we saw their needs that's why on the 28th we'll be there but now with the government directive we won't go as a group we'll just deliver the products hoping they will be of help to them all right so uh have you done this before just delivering the goods without interacting with the people is this something that has happened before no no actually this is the first time this is the first time all right because we we want to avoid having a group of people congregating at a children's home because we also want to keep them safe keep them safe and keep yourself safe in the process uh so uh what is the importance of just interacting with these kids while uh helping them out giving these things giving out these things that that they need this interaction this social interaction what is the importance of that well what we dis or what we we do is that we show them that there is more to life what maybe they see it's good to show them that uh a number of people out there do actually care for them that's why actually we do three things when we visit our children's home uh in in in simple words fun word and mentorship so we have fun we pray together we interact with them we feed them uh if we can and of course the word of god we give them we we we always have a preacher goes with us everywhere we go so this preacher gives them the word in an interactive manner the way they can understand so that even if they're in a children's home they can know that the love of god is actually sufficient no matter where you are and number three is mentorship we make sure that we we work with them we know what they need and we show them we we've been somewhere before and we actually here so it can actually work for you all right uh why is it important to you that you pass the message of of the lord uh to these kids uh do you have a backstory do you have a story uh special story with the lord that that inspires you to share uh it with those kids well uh this is what i believe that everything you do in this world uh no matter where you are it's a seed and uh i've always uh meant to remember that the harvest is always greater than the seed for instance you only plant also three seedlings of maize but you you get the the whole whole whole whole kind of maize so uh that's why we we do what we do so uh telling them the word of god or sharing them the word of god this is what we believe as quench foundation there is no greater mentorship than what the word of god says about a person so if you can do all things through christ to strengthen you if you can understand that i believe you'll be able to conquer the different adversities of life all right it seems like uh made a huge mistake to ask if you're christ but you're really good at this and i like uh i like how you're handling it so i'd like to know there's an assumption that every child in a children's home is an often have you met other uh other cases that uh that are different yes actually like uh where we are going on the 20th it's actually a rescue center it's a place whereby maybe uh children go when they can't live with their families because of different reasons uh kids from the streets so actually it's not only orphans who are in their children's home there are people their parents maybe went abroad they left their children somewhere without someone without a guardian so these people are taken in by the government and they are taken to rescue centers so that's why we come in and we start helping so not the notion of the traditional understanding of a children's home is that it's for orphans but actually it's not all right yeah so uh the big question is always uh uh where do you get all these things cost money even traveling to limuru cost money where do you get all this uh funding from and is it sustainable yes um okay we we've not been doing these what we do for a very long time we've only been into about three or four events so far uh so um i would say sustainable because we are working with a group of partners our members people who we subscribe to the same notion of giving so i would say it's uh it will continue because these people are willing to give remember it's not about how much you have it's about what you can so if you are talking of foodstuffs if you are talking about shoes and so forth so on remember um it's very easy for now to keep a young girl in school because with 200 shillings that particular young girl will be able to go to school for a whole month without this kind of without the hiccups yeah so um i would say sustainable it's it's it is sustainable all right uh so if anybody would like to be part of quench foundation or whatever you do uh either physically or remotely how can they get to interact with you your camera is number four well um if you would like to join quench foundation kenya it's pretty simple uh we have you can visit all our social media platforms at quench ke twitter instagram facebook uh we are at quench ke and you'll be able to find ways into which you can join quench foundation all you can call us uh on 0703 763 169 and be able to interact with one of our publicly relations uh manager all right waiting by the way to take your call thank you very much for that and remember your social media as well uh right for a four channel on twitter right for a four underscore channel on instagram and right by four on facebook hashtag is one the morning hashtag is entrepreneurship tuesday and never ever ever forget tell us where you're watching us from and twitter and facebook we have a question for you how is it working from home how is it working from home now that we have to be safe or stay safe from the corona virus tell us and we'll be very happy to sample them in the course and at the end of the show back to you my brother uh so is this what you do full time well this is not what i do full time but it's something which i would love to do to do full time yeah you know there is a famous story by bill gates uh if i can recall the the story once upon a time he landed in a certain airport and someone asked uh is there someone a journalist by the way is there someone who is richer than you are so for the first time this guy didn't have any amount of money to buy the newspaper so this guy who was selling the newspaper gave him that particular newspaper for free bill gates landed in the same airport for the second time um coincidentally he didn't have enough change to purchase the newspaper so the same guy offered to give him the newspaper and the guy told him i'm actually operating on a profit i won't go on a rose if i give you this newspaper so after a while bill gates became rich the man he is today and he went back to look for the man and he wanted to give the man uh he wanted to give anything that what the man would ask bill gates wanted to offer so he looked for the man after some few months he found the guy so he asked the guy what would you like me to do for you the guy asked him a simple question i gave you i gave you when i didn't have nothing now you want to give me because you are rich would you are giving and by giving be equal so the guy decided so bill gates learned one lesson that there was someone actually richer than him because he was willing to give when he had when when he could not when he had wow so uh even a newspaper vendor can teach bill gates something yes so you can always learn something from anybody anybody all right yeah so you can always learn something from every single person knows something that you don't yes and actually you know if you have a hundred shillings you can always donate 20 shillings not only to quench foundation we have so many other things that you can do like i've learned that jack ma has donated some stuffs to to the country to continue with the fight against this coronavirus so people are continuing to give and actually people are going to supermarkets and buying stuff nobody's remembering these people in nursing homes and children's home so maybe it's a wake up call to everybody to also as they remember themselves remember someone today remember someone today that is a message from the quench foundation and the message is simple remember someone else and give because you can don't give because you have wonderful remind them your social media handles again and how they can get to be part of this as we wrap up well at quench ke across all our social media platforms on twitter instagram facebook uh you can find us at quench ke and of course you can call us through or seven zero three seven six three one six nine and there's someone waiting to take your call right now all right thank you very much for coming through and i really appreciate you i really appreciate what you're doing and keep doing what you're doing right there i see you have something uh what is that well at quench foundation kenya we have one of our characters is to give or we decided to give you something so that you can become one of our brand ambassadors okay quench foundation kenya and what we do is we impact our generation so from today you will be i'm an official ambassador yes it's my honor it's my honor to be an ambassador thank you and despite the coronavirus i have to shake your hand for that thank you very much i appreciate you and i keep doing what you're doing officially branded and i'm officially an ambassador of quench foundation you can find them online as a foundation and you can be part of what they do right there so thank you very much for coming through we appreciate you and on behalf of y244 why in the morning we ask you to give uh because you can don't give because you have and another lesson i've learned from the brother right here is that you can learn from anybody else you can learn from anybody everybody out there knows something that you don't so when you wake up in the morning it's a brand new day to learn something my name is barry mosses or it's my morning every social media platform and we'll be back with tomorrow why in the morning don't go nowhere


Are you ready? I don't know what I've been for at all. We've never recorded a video together. Never. This is a different experience. It's different. I'm shining in them entirely.  Welcome everyone, hi. I'm your humble host, hot, hot man. I'm here with the beautiful, the bountiful. The, give me another beat. Bombastic. Bombastic. Buxom. Buxom, what is that? It means big boobs. Nontrae from the twitch.tv world. We were asked by the great old internet, what's the craziest food you've ever eaten in combination with each other?  I didn't know you outsourced this one to the internet. I didn't outsource it to the internet, but Jocelyn did outsource to friends of mine that work in the restaurant industry or are currently chefs. I don't want to call them out, but I feel like pregnant women especially have very strange food combinations. You're gonna ask my sister-in-law. Yeah, it's too late. Fuck! You missed the window by this watch. I missed the window. Well, she's currently in there. Exactly. Wait, there's still time. Get her out of the way. There's still time. I'm sure she would appreciate a FaceTime call for me right now. Hey, what are you craving? She's just screaming. Nebendurl. I don't know any of these food combinations. You don't know any of these food combinations. Actually, I do know one of them because I requested it. Have you ever put yellow mustard on mac and cheese? I like yellow mustard. Do you like mac and cheese? In mac and cheese, it's a little strange, but I'm not opposed to this one. Bring it out, Jocelyn. Yeah. Yellow mustard, mac and cheese. Yellow mustard, mac and cheese. Yellow mustard, mac and cheese. Yellow mustard, mac and cheese. No! This is like in the class of like things I would try in the cafeteria, you know? She's already mustied up. Oh, yeah, there's mustard. This is not the mac and cheese that I requested. Excuse me? It's mac and cheese. No, no, no, no, no, no, no, no, no, no, no, no! These mac and cheese, the white cheddar Annie's mac and cheese, it's the purple box. Yes, I did. Those are good. I asked for Annie's mac and cheese, the white cheddar with the purple box. What are you even filming? Cheers. Wow. It's not as good as the white cheddar. I think the white cheddar actually would have really paired well here with that. This is more mustardy than it is cheesy. I think you're right. I think the ratio of cheese to cheese to mustard is all off because of the kind of cheese. You know, this is whatever this is, you know, American yellow stuff. But if you went with a nice, like a purple box, I'm envisioning every box, some sort of purple box. What is that? Cheddar? Cheddar, mild? Some kind of shell shape. Yes, a white cheddar maybe. And maybe it's something that I already actually asked for. We'll never know. I think I asked you in person, so you can't prove anything. What's our rating scale? We should know that out. Do you want to be just the basic one out of 10? Yeah. Is inoffensive. 10 is like really good, right? 10 is like, I would make this for a loved one. Are we going stars? Should we do? Can we do Neo? I feel like we can do shells. But not everything's gonna be American cheese. Yeah, but we could rank everything in the shell shape just to rub it in. Yeah, you can do a white cheddar, Annie's American cheese white cheddar shell or you can just do that classic purple box. We can four and a half Annie's white cheddar shell purple boxes out of 10. Yeah, four and a half Annie's white cheddar American cheese boxes. Bring on the next. Whoa. I thought you were pulling something out of the dishwasher. Yeah, dishwasher meat. This is like a Midwest classic here, but I'm pretty sure it's supposed to be cheddar. Pretty sure it's supposed to be white cheddar from a purple box.  I don't want it. We should not have said all that stuff about the white cheddar, huh? It's not bad. I didn't even taste the cheese. I'm going in for a second. You know what the problem with it is? It feels like I'm chewing flubber, like it's so gooey. Yeah, it's real gooey. The only thing that's gonna get me today I think is textures. There was really not a lot going on here. Not a lot to be desired. It just tasted like pie incredibly. I cannot believe how little American cheese came through. Yeah, I think that's a solid middle ground. A solid five out of 10 mac and cheese boxes. I like this more than I liked the mac and cheese. Yeah, by .5. It looks heinous. It's just not look okay. I had to really like look away while chewing because I think that really did me a...  A lot of the bugs really don't taste like anything, but you just have to not look at it and you have to remind yourself or tell yourself that you're not actually eating bugs. I kind of mixed a couple of things, but it's all in butter with pickles. All in butter with pickles? Did you ever have peanut butter with pickles? I'm not a peanut butter lover. That was not my thing growing up. Any question? How come there's turkey and cheese in it? I combined it. So people do pickles in peanut butter or peanut butter in like their burgers or the sandwiches and just combine all those. Peanut butter and... I've had it. It's actually kind of good. Peanut butter and savory stuff isn't too strange, you know? Penang curry. I'm good. The pickles are kind of overpowering, which I don't mind because I like pickles. You know? It's a texture thing. Bad? It's just not much more gooey. There's a little loop in here. But I can't keep smell. I keep wanting to get hits off of it. I can't smell anything anymore. Maybe smell mine because your pickles are so big.  Oh, yeah. I should get a bite of each other's sandwiches. You want to do that? Do the wedding thing. Yeah. You want to do that? How do you do that? This just goes back to me. We're biting our own. Nothing says romance like sharing your almond butter, turkey, American cheese and pickle sandwich. Oh, baby. I'm juiced on this one. What do you mean? I know what this is. What do you mean? Wrapped in fruit roll-up with gutters. You've never had that before?  Dude, did you have a childhood? You are in for a treat. That's the sword in the stone. You got to have a delicate touch. Oh, God. I don't like the way this is. Yeah, it's stuck. Can you tilt it? Dude, you have to do that. Trust me. Can you read the sandwich? Oh, yeah, the sandwich? The sandwich was like a three. The sandwich was the worst one, for sure. Yeah, it's just like there was nothing about it that I liked. Watching you just purple-nurple this. Oh, no, no, no. You've got to stop playing with your food. Eat your fruit roll-up pickle. I got it. We give you extra gushers. I got it. I got it. I'll take some of these. Put them back in. It's a little botched circumcision, looks like. You bring it around town. OK. I would cheers you, but I don't want you to destroy it. You don't like it? I kind of like it. No, thank you. I don't like the way it fruit roll-up sticks your teeth. True. You got to like that. I don't like it. I love gushers. I love pickles. I love to roll up. This is going to be a lot of jam hot. I would have to count for it. This is definitely napkin core. This might be a snack that you have to take a shower after. Here, it's slightly wet. That was epic. That might have been the coolest thing I've ever done. Next meal. Next meal. What would you rate that one? Oh. Personally. Because this is going to be the first one I think we divert. I'm going to rate this two. A two? The worst two? 0.86. And you better make the math right, Justin. That box better be 86% of the way. I'm going to give this one an 8.73 repeating. Wow. I think it was really good. I love pickles, like weird pickle flavors, you know? There's like pickled lemonade, Kool-Aid pickles. Do you have any foods that you're afraid are going to come up? I have one. Was that the one you texted me about? Yes. The cottage cheese? Yes. I'm going to eat it if it's on the table. It has to be consumed. Well, I will eat it. I'll double down for you. You'll take? Yeah. I really, I just don't want anything super jello. I just don't like jello. Really? It makes me want to throw up. It's just, it's the consistency of it makes me want to die. So we've done three so far? Four. Four? We have 11 more dishes. I feel good for, for, for what? A third of the way, a quarter of the way? It's a 15 course meal. We're going to have to decide if we're going to head on a Michelin star here at the end. Oh. Did you know that Michelin stars came from the Tire Company? Did you know that Erick, Erickorn breaks his toe in that thing or the rings? Oh, my God. Is that A1 sauce? A1 and cottage cheese? Oh, why? At a sleepover once, I thought I was getting raspberry yo-play and it was cottage cheese. And I ate it thinking it was yogurt. So imagine going in for a bite of yogurt and it's cottage cheese.  I spiked it in the garbage can and then I angrily went to bed first at the sleepover.  Pick me up. It's five in the morning. I'm done. That is so bad. You don't have to do this. I have to do this. I need to do this. Bites. If you did the show, I'm doing the bite. If you must. Yeah, I got to do it with a spoon because I don't want to tape this. See, it looks devious. This is really bad and I like cottage cheese. I think I can make it to the bathroom time. Well, there's a sink there. The last time I had cottage cheese, I had to get obliterated drunk. That was the plan, was be blackout so I didn't know. Orsel. Why does it look tangy? Makes it easier for me because it's so strong. It's really overpowered. I'm giving it a 0.7. I'm giving it a skull in crossbones. Just flaming skull in crossbones. Again, these are things that people do. This isn't just random food thrown together. I mean, I guess at one point it was. This is stuff that people do. It's in my teeth. I have to.  I got to be prepared. How did eating that make you feel? It reminded me of my grandmother's funeral. Mother's vagina. I saw his grandmother's vagina. This is your favorite rice and ketchup?  This looks like the target logo. Why'd you do that? I don't really like ketchup. I don't either. But this could maybe work. Okay, hear me out.  Campbell's tomato soup and rice. It literally tastes just like it. Campbell's tomato soup. Campbell's tomato soup is way too ketchup-y. They put too much ketchup in there. I think a reason why I have a hard time eating ketchup sometimes when it's so much ketchup, I would make videos of my friends growing up and we would make fake blood out of ketchup.  I'm ready to add three out of ten. Three! I'm going to be honest. I think that's the second best thing I've had today. I don't love it, but I don't hate it. I'm going to give it 6.6 almost the number of the beats. Actually, I'm going to rate it higher than the sandwich. I'm going to give it a 5.2. It's close on butterscotch pudding. What? I didn't even know this is a thing. Butterscotch pudding? I thought that's the only thing in Undertale. Smells nice. It does. It smells like a candle. Well, here we go. A little bippy. I'm going to go full submersible here. Very dessert-y. Yeah, that's not bad. But also, I don't know if I've ever been in a place mentally where I would want to try this. This is a really bad breakup meal. You're right. This is not a snack. This is a meal. This is girl dinner. I'm going to give this a 7.5, I think. Yeah, that feels good. It's really not bad. What are you doing for this? I think 7.5 is a really good rating for this. Okay. Is this a male? Is this Hellman's?   No, not really. You're either on the big male guy. Yes. You do it. You do it. You let me know. You're going to love it. What is up with that? It changes everything. It feels like getting taste. It keeps going. It does. It lasts forever.  It's terrible, but I could see why somebody would love it. Mitch McConnell would love this. This is what Mitch McConnell ate before he paused. I'm giving that a 2 point. I'm going to give it a 1 and 2.5 Mitch McConnell's. This looks awesome. These are flamin' hot. Flamin' hot Cheetos. It's stirring. I feel like this might be good. This one I have really high hopes for. I've never heard of this as an idea. I think that this could be the key. This is the missing link. This is a keeper. I don't mind it, you know? I don't mind it, but do I crave it? It's like, would I eat a spicy strawberry? Yeah? I think I would. I think this might be the best of the bunch. I'm going to give this an 8. I think it's just under the picklezilla. This is going to be an 8.32. What was the other one? A tenth of a decimal under. A tenth of a decimal under. Come on, bro. I'm not doing it. I love your squirt pattern. Look at that squirt pattern. I'm just going to take a dip here. Oh, God.  This? There's no way that this is good, right? I want to level it up. Oh, you're going to do a smear? Can I have the bottle of ketchup, please? Ketchup? Bah, mustard. This is how they make them.  Well, best of luck. It's not good. I don't like it. These are pretty inoffensive, in my opinion. I'm thinking like a 5-ish area. Yeah, I think 5 even. Yeah, 5 even. This feels like right in the middle of the road. I don't want to eat more of them, but I can't eat one if I have to. I've got to say, there's a treat brewing in me. Why is there so much mustard? That's what they say. Okay, so I already don't like watermelon. It kind of looks like tuna. It does. Wow. This looks like, literally looks like a $40 sushi thing. I'll take the big piece. You've got to have a full even coat. It doesn't smell bad. I kind of think this one might work. Of all the mustard experiments. I don't know why I thought that. I don't love it. The watermelon is so juicy that it just makes like mustard water. How many more dishes do we have? Four. That one made me see God. Listen everyone, thank you so much for watching this far in the video. We're going to take a slight break. Justin, we're going to throw it to you. You're going to do a nice little ad read for your new product that you're selling, Justin. So take it away. You have fun with this one. I made so much mud. Is this more a one? Balsamic? I feel like it could work with the right flavor, but right now the smell coming off this thing is like putting my nose in an ox's tachas. Very interesting. We'll get a little bit of mustard in this as well.  It starts off really salty and then it kind of turned to caramel. I kind of like that. It starts off really salty. Really, really salty. Like it kicks you in the face and then it chills. When you have Ben and Jerry's, you grab a pint.  I do. If you don't, did you even get the pint? Exactly. This, I think, is the best dish so far. The only reason why the pickle is better is that I finished the pickle. That was a solid 8.7. I'm going to give it 7.7. So this is an actual snack we eat in Mexico. This is called Hosty Locos. Hosty Locos. This looks awesome. It's kind of like ceviche. So what's in this? So there's cucumber, tamarind candy, there's tamoy, and then the white things are cooked rice. This actually looks and smells awesome. Very messy. Which I'm here for. Okay, it comes back around, actually. At first I was like, I don't think I like that. It is such a one more bite, one more bite. Yeah, that's actually really, really good. I'm giving that a 9.8 3 7. Definitely the best thing we ate. But did I like it more than the pickle? And I think I did. I want to give this one a 9.08 9.08. Do you know that there's a family in there eating chips and salsa? Did you know that? On the logo. There's a little family eating chip and salsa. Is there really? Oh my god. Right there. There's two people eating chips and salsa. Have you noticed that before? Did you know that there's an arrow in the FedEx? I also kind of feel like that was the calm before the storm and now we're entering just hell. Are you scared? I feel like existential dread right now. I also did say the last one is really gross. The worst by far has been the cottage cheese. The cottage cheese was so heinous on so many ways. We have something worse than the cottage cheese. What? Worse? What is an otter pop? Like a popsicle? The frozen thing? That pickle is... Is this a huge pickle? That pickle is well below average. Did you put this in the freezer? I eat it. It looks like somebody's thumb. I'm going to go from the end. I don't know if that's the strap but I'm going to do it. I don't want to go off. That's just because it's cold. It's actually not that bad. It's looking neon green inside. You're not even going to pick it up. What is this?  Dude, you got to try it. I'm telling you, it's great. I can't back into it. Be gentle. I don't think I can eat the whole thing. No way. No one could. It's not bad. I really kind of like it. There's so much going on. In the head to head pickle fight I think I'm going to take the fruit roll-up pickle. I really like the fruit roll-up pickle. I might go eat one at home. I'm going to say a solid 7.8. I'm going even 8. I would never order it but if somebody offered me a bite I'm happily accepting. Wait, this is the last one isn't it? This is the worst. Oh my god, is that Pepto Bismol? Is this Pepto Ice Cream? What color on that thing? I I am excited. I love Pepto Bismol.  You could smell the medicine off it. I'm surprised we could smell it from the other side of the wound. How many doses of Pepto is this? No idea. Just did the whole bottle. The noise off that gave me goosebumps. Oh god. This could be less on my sleep. It's been a good running. Clink. It's not awful what is the thing? It just tastes like Pepto Bismol because it is. It's just Pepto. Why did it texture feel like eating sheets of ice? Yeah, it did. Why do I love it? He had a brownie with Pepto ice cream on top of it. It'd be kind of sick. That was better than I expected it to be. You want to blend them? The mega blend? Yeah, we got it. It just needs to be done. What if this is what grows my hair back? Is this going to blend? Oh, it'll blend. Don't be shy with those. That might be the hard thing that saves us. I've gotten a whole mustard watermelon. This is the silliest thing I have done in a while. And of course, how could we forget ketchup rice? The side profile on this thing is otherworldly. Lovecraftian. Are you ready? Yeah. Put on some LD. Put some liquid death in there. Just a little sparkle.  It is heinous.  I'm not a religious man. This could do it for me. Timothy, shall we eat your heart out? Look at the texture on that thing. Take a seat. Please. Come on, look at the legs on that. This is what everybody turns into at the end of Evangelio. Oh my god. The smell is so bad. No. We don't have to drink all of it. No. Take so long. It's so long. Just burp so hard. I farted. It's gonna come up, but I just it's in your mouth. It's just all I think it's okay. At least smell it. Please, please smell. I don't think I can. Thank you all so much for watching this video. Make sure to go check out Nadre. It'll be the link in the description. He is a great streamer. Make sure to go check him out. We'll see you next time. Don't forget like and subscribe. Thank you so much for watching. Okay, we can cut. Oh, we don't need to.


Elon Musk compares idea of Ukraine joining NATO to nuclear apocalypse. American businessman Elon Musk believes that Ukraine's accession to NATO may lead to nuclear apocalypse. This is literally how the nuclear apocalypse movie starts. He wrote on his ex-page under a post with a video of a speech by US Secretary of State Antony Blinken and Ukrainian Foreign Minister Dmitry Kuleba, during which the top US diplomat said that Ukraine will become a NATO member. Musk dubbed his comment with a link to a clip from the 1983 feature film The Day After, which features footage of a fictional nuclear war between the Soviet Union and the United States. Earlier, NATO Secretary General Jens Stoltenberg reiterated that Ukraine should become a member of the alliance but said that he did not know when that would happen. US Secretary of State Antony Blinken said that more aid is urgently needed for Ukraine following meetings with NATO foreign ministers amid growing concerns that Russia is building up its defense industrial base with support from China, North Korea and Iran. Ukraine applied to join NATO on a fast track basis in September 2022 and was assured at the alliance's summit in Vilnius in July 2023 that it would be admitted if the necessary conditions were met, but no timetable for its admission was given in Brussels. Meanwhile, the organization has repeatedly pointed to the fact that Ukraine's accession is impossible while the country remains in a state of armed conflict. NATO now includes 32 states, almost all European countries, Canada, the United States and Turkey. Bosnia and Herzegovina participate in the program for admitting new members to the alliance. In order to join NATO, a country must meet the conditions of an additional plan, have no territorial disputes and bring its armed forces in line with the alliance's standards. Biden is a bigger danger to US democracy than Trump, Robert Kennedy Jr. President Joe Biden could be a bigger danger to US democracy than former president and presumptive 2024 election rival Donald Trump. Another presidential candidate, Robert F Kennedy Jr. has said Biden is the first president in US history to mobilize federal agencies to silence his political opponents, the politician stated. Speaking on CNN, Kennedy Jr. pointed to his being blocked on various social media platforms during Biden's term in office and branded this as an effort to censor political speech that violated the First Amendment of America's Constitution. He also attributed the censorship to pressure from the White House. Kennedy stated that he still views Biden as a bigger danger even though Trump played a role in the January 6th riot at the US Capitol. The question was, who is a worse threat to democracy? And what I would say is, I'm not going to answer the question. But I can argue that President Biden is, because of the First Amendment, Erin is the most important. The candidate told presenter Erin Burnett, I can make the argument that President Biden is the much worse threat to democracy and the reason for that is President Biden is the first candidate in history, the first president in history that has used the federal agencies to censor political speech, so to censor his opponent. The politician's Instagram page was suspended in 2021 over what its parent company Metta described as repeatedly sharing debunked claims about the coronavirus or vaccines. The account was reinstated in 2022 shortly after Kennedy announced his election campaign. Kennedy, 70, is the son of former US Attorney General Robert Kennedy and the nephew of former US President John F. Kennedy, each of whom were assassinated during the 1960s.


As we know, agriculture is the primary source of livelihood for more than half of the Indian population. And the nationwide lockdown has affected many of them. Although there are no latest official records, it is considered that Tamil Nadu alone accounts for more than 75 lakh farmers. According to the National Horticulture Boats Database 2014-15, five states Gujarat, Tamil Nadu, Maharashtra, Andhra Pradesh and Karnataka were involved predominantly in banana production. As per a report, Tamil Nadu ranks second in banana production across the country and is fifth largest banana growing region in the world. According to the state's Agriculture Department, the average banana yield in Tamil Nadu is 100 metric tons per hectare against a national average of 37 metric tons. The state's annual banana production is 6.2 million tons with 3 lakh hectares under cultivation. Tutukharin, Theni, Tiruchrapalli, Coimbatore, E-Road, Tirinalveli, Kanyakumari, Khadalur, Thiruvannamalai and Tanjavur districts predominantly produce bananas. The banana farmers have suffered huge losses during the lockdown. To understand their issues, news click reach them at their fields in Chola Vandan village of Madurai near Theni district.