Can you imagine that? He's turned ten perfect handsprings in a row! He's terrific! He's feeling his Cheerios! Yes Cheerios, the breakfast cereal made from oats, good old fashioned nourishing oats all ready to eat. And now the Lone Ranger brought you by Cheerios! A fiery horse at the speed of light, a cloud of dust and a hardy-high old silver, the Lone Ranger! Yes, when you hear that galloping horse, it's the Lone Ranger!  It's Cheerios!   It's nourishing, really nourishing! We recommend Cheerios for every loyal follower of the Lone Ranger because it gives you a kind of nourishment that really counts. Remember for a better breakfast, start with Cheerios! With his faithful Indian companion, Tonto, the daring and resourceful masked rider of the planes led the fight for law and order in the early Western United States. Nowhere in the pages of history can one find a greater champion of justice. Return with us now to those thrilling days of yesteryear. From out of the past come the thundering hoofbeats of the Great Horse Silver! The Lone Ranger rides again! The young man who sat inside the stagecoach was quiet and unfriendly. Though Dan Reed, young nephew of the Lone Ranger, had ridden many miles in the same coach, no words had been spoken. Finally, as they neared Frontier Town, Dan decided to break the ice and start a conversation. We'll be in Frontier Town soon, sir. I know. Is this your first visit there? Yes. My name's Dan Reed, sir. I live near Frontier Town with friends. Really? Do you know anyone in town, sir? There's Rimrock Bridge just ahead. After we cross that stream and then the railroad tracks, we'll enter Frontier Town. Does the stage stop near the hotel? Oh, yes, sir. It stops at the Sunset Hotel. Thanks. But if anyone comes to stay a long time, they take a room at Mother Willard's rooming house. That would suit me better. I can show you where it is if you want me to, sir. We're going across Rimrock Bridge now. You better get my things together. That small bag on the seat there's mine. I'll hand it to you. Gee, I'm sorry. I dropped it. Why do you have to be so clumsy? Pick up the things and put them back in. Yes, son. Let them alone. Golly, I was just trying to...  None of your business. Why do you have to be so snoopy? Golly, mister, I didn't mean to... Quiet. The nerves are rather jumpy today. Oh, that's too bad. I'm sorry. Idiot! You'll like this, Tom. Dr. Umin could use some help. He's the only doctor in town. See here, Dan.  I'm a salesman, not a doctor at all. Oh, as a matter of fact, I was starving off here to see Dr. Drummond because of an order he sent in about new instruments. Oh, I see. My name's Garwood Ellis. Glad to know you, Mr. Ellis. We're almost to the hotel. I'll help you carry your luggage and show you the way to Mother Willard's rooming house. That's the rooming house just ahead. The last house on the side street. That'll do very nicely. There's a quiet section of the town. In here, sir. It's way out at the end of town. What are those hills out there? Those are the Enchanted Hills. What can I owe you, that boy, Dan Reedan? That's right, Mother Willard. I brought Mr. Ellis here. He wants a room. Glad to meet you, Mrs. Ellis. Thank you, Mrs. Willard. If you happen to have a room... Now you just call me Mother Willard, like all the rest do, Mrs. Ellis. Figure on staying long? I don't really know how long I'll stay yet. Have you been on the stagecoach from the east? Yes, I did. Now if you'd be kind enough... Where'd you come from? Well, look, man. If you don't have a room for me, perhaps I'd better go back to the hotel and...  Lensakes, nobody takes offense at my questions around here. Just my way of being friendly, stranger. Dan can tell you that. That's right. But Mr. Ellis is tired after the trip, Mother Willard, so if you'll show him... Yes, he is. I should have thought of that. Come right on in. I'll give you a nice, comfortable room all to yourself. Good. Thanks, Dan, for helping me. I can manage the luggage now. All right, sir. Maybe we'll meet again soon. Of course you will, Dan. You come around any time you feel like it to see us. Thanks, ma'am. I'll be leaving now. Bye. Goodbye, Dan. I declare that's about one of the nicest boys around here. I don't know anything about his folks, but I certainly like Dan. Yes, I like him, too. He's very friendly. Now, if we can go inside... Oh, Dan, thanks. Of course we can. Come right on in, Mr. Ellis. I'll show you. Dan Reed went to the livery stable to get his horse, Victor. It was almost dusk when he arrived at the camp he shared with Tonto and the Lone Ranger in the Enchanted Hills, several miles northeast of Frontier Town. Ho, Victor! Ho, my ho, ho! Well, Dan, welcome home. They missed you. Well, thank you, sir. I sure missed you and Tonto. How, Dan? Hi! You have good time with Thunder Martin, Barrow Bell? I sure did, Tonto. Those two keep me laughing all the time. Me like them. Them plenty good company. Yes, and they're mighty good friends to all of us. And to each other in spite of their differences. Now, stage must have come in late, Dan. You take long time to get here. Oh, the stage was on time, but I showed a man on the way to Mother Willard's rooming house before I left Frontier Town. Someone from the stage, Dan? Yes, sir. He's stopping off here to see Doc Drummond. His name is Garwood Ellis, and he's a salesman. Salesman? Yes. He had a little bag that fell open. It had doctor's instruments in it. I thought he was a doctor at first, and, well, he seemed to make him angry. Then he told me he was selling the instruments. Strange you should be upset about that. Also strange about him stopping off here to see Doc Drummond to try to sell him medical instruments. Why, sir? Because, Dan, Doc Drummond has a kit of fine instruments for one thing. The other is that there aren't enough doctors in the whole western territory. It makes such a trip out here worthwhile for any salesman. Well, that's right, Dan. Golly, then I wonder why he told me that. I wonder the same thing, Dan. If I was my curiosity, I'd like to make it a point to know more about Garwood Ellis. A few days later, Dan and Tonto were in the general store buying a few supplies. Oh, is there anything else? No. No, not all for now. All right, here's your package. Here comes Mother Willard, Tonto. That's Mother Willard all right. Well, for Dan's sake, Dan, read. Morning, Mother Willard. Oh, this is Tonto. How are you, son? Thought you were coming round to see that friend of yours, Miss Ellis. Well, I haven't been into town since Mr. Ellis arrived. How is he? To tell you the truth, I'm worried about that young man, Dan. Moves and paces in his room all the time. Hasn't been outside since the day he come there to my rooming house. He hasn't? We said he was going to call on Doc Drummond. Matter of fact, Doc Drummond came to the house yesterday to see one of the rumors. Oh, he did? Well, maybe young fellow see Doc Drummond then, Dan. Oh, but no, he didn't at all. You see, being worried about him like I am, I went up and knocked on his room door. He opened the door a crack and asked what I wanted. Gee. Yep. And then we're not holding. Maybe he better let Doc Drummond talk to him. He says, please, Mrs. Willard. He won't call me Mother Willard like the rest. Please, he says, I know you mean well, but I'd rather you let me handle my own affairs. I don't want to see anyone, understand? And then he closed the door at my face. Collie, I wonder why he's like that. Been trying to find out what's wrong with him, but I can't make much headway. You see, he won't let me in to clean his room. Said he'd do it himself. He even takes his meals in his own room. But I can't understand why he wouldn't talk to Doc Drummond. We're ready to go now, Dan. Oh, yes. Well, goodbye, Mother Willard. Give my regards to Mr. Ellis when you see him. Yes, I'll do that, Dan. Goodbye. Goodbye. And now I die. Oh, yes. Dan, you put supplies in saddlebags while we go to Sheriff Taylor's office. Maybe him having some new handbills for loan rangers. All right, Tonneau. I'll meet you at the hitch rack. As Dan waited at the hitch rack, he saw a horseman galloping into town. The man drew rain when he saw Dan. Move! Move that boat! Hey, boy! Hey, kid! Where'll I find Doc Drummond? Up the street, opposite the Sheriff's office. What's happened, mister? Some sort of epidemic broke out over at Rock Hill. It's getting bad, and we don't have a doctor there. Hello, Hope Doc Drummond's in his office. He didn't have a gore. Golly. Well, we're ready to go now, Dan. Now, what man on horse say about Doc Drummond? There's an epidemic over at Rock Hill. He's come here for Doc Drummond. Oh, that's not good. Come, we go to a loan ranger. Hey, boy! Hey! Come on, Victor, and I'm up to town. No time later, Dan and Taunton arrived at the camp where the loan ranger was waiting. Oh, perfect! Oh, say what? You both seem to be in a hurry. I think we're all in town. A man came to Frontier Town looking for Doc Drummond. There's an epidemic in Rock Hill. That's right, Kimisabi. Did he say what kind of an epidemic it is, Dan? No, sir. Let me see him talk to Dan. He looked like he'm plenty excited. Yes, he was. Oh, oh, me forget. Let me stop at Sheriff's office to bring two new handbills, Kimisabi. Let me see them, Taunton. Oh, here. Oh, this one's about an outlaw who robbed a bank in Pecos. Tall, heavy set with a black moustache, scar and cheek. You'll have to keep an eye out for him. And what other ones say? We not have chance to look? Well, let's see. I wanted for murder Dr. Gary Edwards, 30 years of age, about 5'10 blonde hair. Known to be left-handed. Contact Sheriff Green and Austin with any information whereabouts. Dan. Yes, sir? Your friend on the stage. I wonder if... Oh, he has black hair, sir. He's not a doctor either. That's what he'll tell you, Dan. Remember what Mother Willard say about him? You tell Known Ranger. What did she say, Dan? Well, she said Doc Drummond was at the house and she wanted Mr. Ellis to see him, but he refused. I see. But didn't he tell you he was coming to Frontier Town to see Doc Drummond, Dan? Well, that's right, sir. He did say that. Mother Willard says he hasn't left his room since he arrived in town. Hasn't left his room, you say? That's right. Me here, Mother Willard, say him have meals and room, not letter in to clean up. He's really awfully nice, sir. I liked him a lot.  Dan, he may be a nice chap, as you say, but his actions are far from normal. In fact, they're downright suspicious. Oh, that's right. I can't help but think of him in connection with his hand bill on that young doctor in Austin. Well, golly, I'm sure Mr. Ellis wouldn't kill anyone, sir. Anyway, he's not a blondie. There is easy to change, Dan. He could have died at black. That's right, Dan. Oh, golly. Tonight, Toto, I'm going to Mother Willard's place and pay a visit to Mr. Ellis. Before I leave, I'll know for certain if he's a man wanted for murder in Austin. We'll continue our story in just a moment. Zoe, it's a new win to our conference record for the high jump. He went over the bar at six feet four. He's feeling his Cheerios. Yes, Cheerios, the breakfast cereal that's made from oats, good old fashioned nourishing oats all ready to eat. Rangers, who's the best athlete in your neighborhood? Who's the fellow who has the most strength and speed and endurance? Well, sir, I don't know his name, but I'll bet you dollars to donuts I can tell you one of the big secrets of his success, because whenever you see an outstanding athlete, you can be pretty sure he's the kind of fellow who eats a really good breakfast every morning. How about your breakfast? Would you like to know an easy way to make it better? Here it is. Just be sure to start your breakfast with a nutritious cereal, a cereal like Cheerios, for Cheerios gives you a kind of nourishment that really counts. You see, Cheerios is made from the cereal grain favored by nature. Cheerios is made from oats. One of the very best of all the cereal grains for growth and energy. Cheerios, crisp, golden brown and all ready to eat right from the package actually provides whole grain amounts of all the known important vitamins and minerals of oats. That's why Cheerios is so energizing. That's why it helps so much to build up strength and endurance. Have a bowl of Cheerios for breakfast tomorrow morning. Delicious Cheerios topped with fruit and plenty of good fresh milk or cream. It's terrific. Yes, try Cheerios and see for yourself why so many people are saying he's feeling his Cheerios. Now to continue our story. After having supper in camp with Dan and Tonto, the Lone Ranger mounted his great stallion silver and rode into Frontier Town. Meantime, the man Dan knew as Garwood Ellis sat on the edge of his bed in his room which was located on the ground floor at the back of Mother Willard's rooming house. Suddenly he looked up startled as he heard a thud at the back window. What the... Don't shoot, you're covered. Masked man. I didn't hear you climb in that window. I made certain of that. What do you want? Now that you've got the drop on me... I came here to talk to you. I want straight answers. There's nothing to talk about, especially with you. Why are you wearing that mask? I got the mask. What I want you to do is... All right, go at the door. I'll be right behind it with this gun pointed at you. I'll be careful what you say. Well, Mrs. Willard, what is it? I came to tell you that I'm going over to Rock Hill with an epidemic of dystheria they endop drum and synth for hell. Epidemic of dystheria? But you'll be in danger, you'll get it. Oh, when folks is in trouble, I don't think of the danger. I'll be all right. But I came to tell you you have to go out for your meals, Mr. Ellis, if you don't mind, till I get back. Yes, yes, of course. Don't worry about that. Oh, the land sinks. It's right. Nice of you to feel that way about it. Well, I'll have to hurry along now. Good night, Mr. Ellis. Good night. I heard what Mother Willard said. She's a very brave woman to go there. That's right. She is. She said Dr. Drummond sent for help. Must be a bad epidemic. He's the only doctor available. So I heard. But to get back to your visit... I have changed my mind about what I was going to say, Mr. Ellis. I can wait. I, uh... I'm going to ride to Rock Hill. I'll be leaving from the west end of town near Rimrock Bridge in 20 minutes. I can have another horse ready if you think you'd care to go and help. No. Why should I? There's nothing I could do, nothing. I'm sure it isn't fear of the illness that holds you back. I don't know what you mean. Maybe you can figure out what I mean in the next 20 minutes. I'll leave now and wait at Rimrock Bridge. Howdy-oes. Take it over. I won't go. I won't. No matter what he says, they'll have to handle that epidemic the best they can without me. The Lone Ranger and Tonto waited near Rimrock Bridge. Tonto had got another horse at the livery stable. The two men sat in silence on silver and scalp for some time. Then Tonto spoke. It looked like he not come. He must have been there. The time is almost up. Maybe you're right, Tonto. I may have misjudged him. You really think him... he can put stuff down. I don't hear anything, perhaps you're... Yes, it must be Elvis, Tonto. Oh, that's good. Well, you win, Mr. Here I am. Glad to see you brought that medical kit with you, Dr. Edwards. How did you know? Never mind that now. Not up. There's no time to lose. You realize I'm practically riding to the gallows for a crime I didn't commit? I'm accused of murder, but I'm... I admire your great courage, but let's go. Come on, silly!  In the cafe in Rock Hill, many of the townsmen talked about the misfortune that had struck their little town. Well, I guess we'll be all right. Doc Jumman from Frontier Towns here and a woman named Mrs. Willard. They haven't all the sick folk moved to the town hall. Let's hope they can keep it from getting any worse. It gets too bad for one doctor that he... He ought to be able to get it under control. No use us getting panicky about it. Well, I've heard that disease fits like wildfire. Yeah, it's been known to wipe out a town. Well, now there's no use looking on the bad side of things. Let's leave things in the Doc's hands and hope for the best. Hope isn't gonna help any. We ought to try to find another doctor and get him here. There's a doctor Meeks in the little town about a hundred miles from here. We ought to send him a telegram. In fact, I'll send him a telegram right now. Then we won't have to worry. In the town hall in Rock Hill, Doc Drummond worked unceasingly over the many sufferers who had been brought into the place. At his side was Mother Willard. Both were exhausted with their continued efforts to stem the epidemic, which seemed to be growing worse. There. Oh, Mother Willard, I'm fighting to stay on my feet. Been at this for 24 hours. I know, Doc Drummond. I only had help. Another doctor. But there's none to be had. My serum's running low, too. When that's gone, it'll be pretty bad. Pretty bad. I...get me to a cot. Quick. Oh, you haven't helped us. You've got it yourself. Oh, here. Let me help you. Let that cot over there. Can't let it get me. Gotta keep going now. Oh, Doc. Doc. Whatever are we going to do now? Meanwhile, back in the cafe, a subdued group of men stood around talking. It's getting worse, that's what. We've had several deaths already. Yeah, Doc Drummond can't handle it alone. We can't find another doctor. We can get to come here. We ought to take our families away from here. Can't do that. Sheriff's orders. Sheriff Taylor from Frontier Town, come over to take charge since our sheriff's away. Taylor says nobody's leaving. Here comes the sheriff now. Howdy, boys. Things getting any better, Sheriff?  Sorry, but I can't allow anyone to leave town. You'd just be taking the epidemic somewhere else. Maybe Doc Drummond will be able to... Hey! Doc Drummond's been put down with the fever. Holy smoke, we'll all get it now. What are we going to do? Sheriff, I'm scared. I'll hold on all of you. It looks mighty bad, but we'll have to do the best we can until we find another doctor. There isn't another doctor within 100 miles. That's right, Sheriff, and he can't leave. We've got a telegram saying so. He's sending serum, but he can't come. Hey, look, I saw through the open door. A mask man just rained up outside. Well, stay right here, all of you. I know that mask man. I'll go out and talk to him. Sure glad to see you, my friend. But things are mighty bad here, let me tell you. Doc Drummond's been put down with a fever, too. Doc Drummond? That is bad. Sheriff, I brought another doctor on this man here. Another doctor? But there isn't any to be had, only Doc Meeks. He's 100 miles away. Nevertheless, I'm a doctor, Sheriff. I came to help. Here's my kit. Then you're the best news we've had today. Better get over to the town hall right away, Doc. Hurry. All right, Sheriff. One cylinder. Get up there. Arriving at the town hall, the Lone Ranger and Tonto went inside with the young doctor. They approached Mother Willard. Mother Willard, I brought another doctor. Oh, thank heaven. A masked man. And Mr. Edwards. The masked man is a friend to all of us. As for me, I'm Dr. Gary Edwards, Mother Willard. I'm ready to go to work. Dr. Gary Edwards? Well, how do you know? No time for explanations now. They can come later. Yes, they can come later. Now we have serious work to do. The afternoon war-on nightfall and the darkness finally melted into dawn. Still young Dr. Edwards with the Lone Ranger and Mother Willard had his side constantly worked without a letter. Other days and nights came and went. The young doctor knew his business thoroughly and brought hope and confidence to the whole town. It was almost noon. A week had passed and he and the Lone Ranger stood with Mother Willard outside the town hall door. Well, I think we've got this late. There haven't been any more deaths in our new cases since yesterday. You certainly know your business, Doctor. He's wonderful. Dr. Unmond is feeling much better too. He says he never saw the likes of you before, Doctor. Here comes Sheriff Taylor now. Everybody's talking about what the new dark's done here. That's right. It's sure like a miracle the way you stepped in and practically stopped this epidemic. Fortunately, I made a special study of this disease. Also, I had a quantity of serum with me. The most fortunate you came to Frontier Town. Look, we come over after having a meeting in the cafe. We voted to ask you, Doc, to stay here in Rock Hill for keeps. We'll give you a house to live in. It'll be a wonderful thing for this town if the doctor will accept. But I... Look, why haven't you told the sheriff what you know about me? I did, Dr. Edward. You did? I sure he did.  Then that's your answer. I'll be going back to Austin as soon as they send for me. Maybe the sheriff has more to say about it, Gary. Yes, I sure have. We've got a telegram back saying that you're not wanted there at all. Well, listen, Gary, I put two and two together. I realized you were the doctor Edward's listed on that handbill Sheriff Taylor received.  All that indicated I was right about your identity. I knew it was easy to dye blonde hair. Now see here, what's this all about? Nobody can say anything about Doc Edward's and get away with it. Easy, easy, Mother Willard. We found out he was accused of shooting a man in Austin. But the telegram says the real killer has been found. Dr. Gary Edwards is innocent. Yes, I tried to tell him I was innocent, but they didn't believe me then. What really happened, Gary? I was in the cafe one afternoon over in Austin. Yes. A man came in and argued with me about an operation which had left his son crippled. He threatened my life if I didn't leave town. That night he was killed from ambush on his way home. I see. I was blamed and had no alibi, so I left and came to Frontier Town. An outlaw who was recently captured admitted killing that man, Gary, so his confession cleared your name. Gosh, I... I don't know what to say. Oh, you don't have to say anything, Doc. Your actions speak louder than words.  I'd buy his courage. Well, what do you say, Doc? Are you staying here for good in Rock Hill? Yes. Yes, I'll be glad to say. Oh, gosh, I gotta go tell the man. You won't regret it, Doc. Now that you've found yourself again, Gary, I'll leave you with your friends. And I'll be back if you need me. Adios. Oh, Lansing. Now I lose you from my room and home. But I'll come to see you often, Mother Willard, and I hope to see Dan again, that boy I met on the stage. I think somehow he's connected with that masked man and helped bring this about by meeting him, I mean. But who is that masked man? He was almost as good as a doctor inside there. Yeah, who is he, Sheriff? You said you knew. Of course I know. The man who got Doc Edwards to come here and did so much for us all is the lone ranger. Oh, too bad. Rangers take this urgent message to Mother. Don't fail to let Mother know. Apple Pie Quick is now selling at a special low sale price. Yes, there's a big sale now at Leading Grocers, a special low price on Apple Pie Quick. Prices have been slashed. Never before could you try Apple Pie Quick at such low cost. With Apple Pie Quick, the family can have an Apple Pie almost any old time. Apple Pie Quick gives you pie crust mix and apple slices too, and the pies in the oven in a matter of minutes. A flaky, crusted, fresh and juicy centered dream of an Apple Pie. So now, tomorrow, take advantage of a sensational price cut sale on Apple Pie Quick. Look for slashed prices on Apple Pie Quick now during this special sale. You have just heard another of the famous Lone Ranger stories, a copyrighted feature originating in Detroit, and brought to you by General Mills, makers of that nourishing breakfast cereal made from oats and ready to eat, Cheerios! Your announcer, Harry Golder. The Lone Ranger is broadcast every Monday, Wednesday and Friday at this same time. Be sure to listen. This is ABC, the American Broadcasting Company.


Box 13, with the style of Paramount Pictures, Alan Ladd as Dan Holliday. My dear Mr. Holliday, I do not address you as Box 13 because having seen your advertisement, I was intrigued and found out who you are. You write mystery stories. I am a professor of criminology at the University. I think I have something of enormous interest to both of us. The perfect crime. I am going to commit it. Won't you be my audience if it pleases you to come to my room? The University. Sincerely, Dr. John Dobbs. At first, I wasn't sure whether the letter was on the level or not. Then when I saw Dr. Dobbs, I was sure it was. And he did commit the perfect crime. Almost. And now, back to Box 13 and Dan Holliday's newest adventure, the perfect crime. Dr. John Dobbs. I never heard of him, Mr. Holliday. Read this. Who's who in American education? Our Dr. Dobbs is quite a personage. Dobbs. John H., professor of criminology and abnormal psychology. Author of over 15 volumes on crime and the criminal. That's enough, Susie. And now Dr. Dobbs says he's going to commit the perfect crime. Is there such a thing? Susie, any unsolved crime is perfect. Oh, maybe he's just kidding. He's a professor. He wouldn't do anything like that. That's exactly what I'm going to find out. At least I'll have an interesting evening. Dr. Dobbs is waiting for me when I got to his rooms. He was a harmless, pleasant-looking man of about old 65. He smiles shyly as he greeted me. Hi.  How long can you stay? All evening. My time is yours. Wonderful.  Well, aren't we all? I suppose so. But let's discuss the perfect crime. Now, what is a perfect crime? One that isn't solved. Yes, yes, of course. But nine times out of ten, the crime isn't planned. I'm speaking about a planned murder, perfectly executed and perfectly hidden. Dr.  Therefore, you should know that no one ever gets away with it. Oh, why not? Because there's always some clue. Some minute trace that leads directly to the murder. Oh, true. But suppose there were no clues, none at all. Ah, but you're leaving out an important factor. And that is? The body. It's hard to get rid of a body. Dr. Crippen was trapped. Trapped because police found the body of his wife in the basement. Yes. But suppose a body could be destroyed altogether. Well, it's never been done. With today's scientific police laboratories, even the tiniest clue can be built up enough to convince a jury. Yes, that's very true. But suppose the body of the murdered person were never found. It always has been. Granted. But suppose it were not. There'd be absolutely no proof of murder. Ah, my point exactly. Now, just a minute. First you have to find a victim, one who isn't even remotely connected with you. Then you have to kill him. Yes, go on. Then having found your victim and killed him, you have to get rid of his body altogether. Those are the conditions, yes. So, after those conditions were fulfilled, you'd have to escape detection and final punishment. And your argument is that with those conditions, the perfect murder would have been committed. Yes. Suppose I told you I can do it. You're asking me to believe the impossible. First, you're a famous man. It's hardly likely you'd risk everything you've worked for just to satisfy an insane whim. Go on. Secondly, I... I don't believe you're serious. But I am. Mr. Holliday, I'm a very sick man. My doctor gives me three months to live. Oh, I'm very sorry. It's no matter. Perhaps he's wrong. No, I know he's right. Then what does it have to do with what we're talking about? Perhaps nothing, except that I'm very tired. I spent a lifetime with books and studying students. I'm a crusty old bachelor. I suppose now I want some excitement. Even my name is prosaic, John Dobbs. Dr. Dobbs, I still don't think you're serious. Maybe you're kidding me for some reason I haven't been able to see or even guess at. No, I... I think I refuse to believe you. What are you laughing at? At what you said. I don't understand.  That's right. Is that funny?  It makes me even more certain that I can commit the perfect murder and win. Well, I stayed with Dr. Dobbs until after three in the morning. We talked, got a marvelous knowledge of crime, and I left him with a great admiration of his intellect. Then three days went by. I heard nothing from him until one day at the office. Hello? Mr. Holliday, please, Dr. Dobbs calling. Oh, oh, just a minute. Mr. Holliday, Dr. Dobbs calling. Oh, okay, thanks. Hello? Mr. Holliday, how are you? I'm fine and you? Oh, pretty well. You remember our conversation the other night. I certainly do. Why? Would you care to be in on the start of my plan?  That's wonderful. But are you free this afternoon and evening? Oh, yes, why? I want you to fly to Chicago with me. What? Will you? I have the tickets on the plane. You're my guest. But why to Chicago? I'll tell you why when we're off the plane. Will you go with me? Yes. Yes, I think I will. Do you like to fly, Mr. Holliday? Oh, I love it, do you? Oh, yes. It gives me a great sense of exhilaration. I am untouchable up here. Why are we going to Chicago, Dr. Dobbs? Here, read this newspaper account of a murder. Police are at loss for clues in the Caroline's standish murder case. All leads have come to dead ends, and why do you want me to read this, Dr.? Because I'm going to Chicago to confess to the crime. Your what? I'm going to confess that I killed Caroline's standish. I don't believe that. We'll be in Chicago in exactly one hour and 20 minutes. Half an hour after we step off this plane, you and I will be at police headquarters, and then you will see. But you couldn't have killed this woman. Oh, yes, I could have. She was killed the day before yesterday. That was Sunday. Sunday's a holiday. It's not too long a plane trip from our city to Chicago, and Caroline's standish is a complete stranger to me. And being a complete stranger, she satisfies the first condition of the victim, that he should not even remotely be connected with her. Exactly. Now settle back, Mr. Holliday. We'll be in Chicago very soon. All right, now let me get this straight, Dr. Dobbs.  Yes, I killed her, Lieutenant. And you? You say your name is Holliday. That's right. Mm-hmm. Well, Dr. Dobbs, we've checked on you since you first came in here an hour ago. We've got quite a bit on you. Your books, for one thing. I've enjoyed those.  It's very simple. I shot her. Oh, what kind of a gun? A .38 caliber. That was in the newspaper. I know. Mr. Holliday, what do you know about this? Oh, nothing except that Dr. Dobbs asked me to come here with him. I see. Well, you can both go home. Thank you, Lieutenant. It's not very often that a murderer's sent home scot-free. Why are you letting him go, Lieutenant? Look, Caroline's standish was killed with a .38. Yes. But two hours ago, we found the killer. He had the gun in his possession. Oh. Then I am free to go. As fast as you can get out the door. Thank you. Come along, Mr. Holliday. I'm afraid the Lieutenant has his killer. And it doesn't seem to be me. So we'll go back home. And then? I'll get in touch with you again. Hello. Mr. Holliday, this is Dr. Dobbs. Oh, you. Where are we going this time? Yes. Guess what? That I'm going to Philadelphia to confess to a murder there. You're going to do what? The same thing I did in Chicago. Will you come along? Oh, no. No, thank you. They're reading the newspaper. You may see some very startling developments with that. Mr. Holliday, I'm leaving for Boston this evening to confess another crime. Holliday, I don't suppose you care to go to Hartford with me. In San Francisco this time, Mr. Holliday, I would like your company. Well, it went that way for two solid months. Dr. Dobbs confessed to every murder that hit the newspapers, and every confession was laughed at. His name gradually became as well known to the police departments of the country as those of the public enemies number one through 20. Then he came to see me at my apartment. Well, Mr. Holliday, what do you think now? Look, Mr. Dobbs, I don't know what you're doing, but please, why don't you cut it out? Oh, are you feeling sorry for me? Look, every one of these newspapers has your name in it. You've made a laughing stock of yourself. Does that concern you? Yes, it does. I admire you. I've read your books and I've talked with you.  Because I intend to go through with what we discussed that first night in my rooms. I don't know whether you're trying to make a fool of me or not, Dr. Dobbs, but I'd rather you didn't count me in on your little escapades. It's no fun committing a perfect crime without an audience. What? I need you, Dan. You're very intelligent. You could appreciate what I'm going to do. Look, Dr., forget all this and go back to the university. Say you did it as an experiment. Oh, well, I've already been given a vacation from the university. What do you mean? The publicity was bad for the school. The president suggested that perhaps I'd been working too hard and needed a rest. Well, you brought it on yourself. Oh, yes, I know.  What do you want? There's a small city about 300 miles from here. Go there with me. So you can put in another phony confession? No, no, no. So I can point out my real victim to you. Say that again. I want to show you my victim, the man I am going to kill, the man whose body will never be found and the crime to which I am going to confess this time legitimately. I don't believe you. Please now go to the town with me. I'm now supposed to be a little cracked, humor me. And if I do? Well, we'll have a little mental chess game, you and I. I'll give you the opening gambit murder. From then on, it will be your job to checkmate me. Agreed? All right, Dr. Dobbs, I'll go with you. But this will be the last time. Understand? Yes, I understand. This will be the last time. Now back to the perfect crime. Another Box 13 adventure with Alan Ladd as Dan Holiday. Well, I went with Dr. Dobbs to the small city. And he took me to a restaurant. He seemed to be looking for someone when suddenly... Look, Dan, there he is. Who? The man I'm going to kill. The one who just came in? Yes, look at him. Describe him to me. I want you to be able to recognize him anyplace under any conditions. What for? Please, please, just do as I ask. Well, I see a man about your build. Yes. A little younger, perhaps. Non-descript. Uh-huh. His name is Alexander Ferris. And he's a buyer for one of the department stores here. How do you know all this? I looked all over for a victim. And then one day I saw him in our city.  Dobbs, let's cut out this nonsense. But it's not. Ferris is a bachelor. He lives in a boarding house. Once a month he takes a trip to our city to buy for the store here. Go on, you're not finished. No, I'm not. I was going to add that Mr. Ferris is going to make one more trip to our city. And that one will be his last. Tell me one more thing. Why did you pick him? Because he seems the logical one. He does things by routine. He stays at the same hotel in our city. He takes the same train there and back home here.  Uh-huh. Now suppose I should walk over to Mr. Ferris and tell him that a mad man is going to kill him. Go on, try it. You know what he'd do. Yes, I think I do. Look at me as though I were the mad man. Then he'd call for the police and I'd be sucking a nice cell until the police decided I was... Exactly. All right, Dan, we're finished here. You've seen the victim, now we'll go back home and I'll let you know when the game begins. Mr. Holiday, please. Oh, just a second. Mr. Holiday, is that man again? Dobbs? Uh-huh. Okay, give me the phone. Hello.  I'm getting tired of it. Mr. Holiday, Alexander Ferris leaves his town this afternoon. He will arrive here at 7.30 this evening off the Lakeshore Limited. He will go to the Barrett Hotel. He will never leave there alive. Hello. Hello, Dobbs. Hello. What do you say this time? Same thing, still hopping on the perfect crime. Do you think he means it? I... He's got me over a barrel. I don't want to believe him. Sometimes I don't, but... But what? That there's something earnest about him when he talks about it. Well, I can't take a chance. I'm going to keep my eyes on Alexander Ferris. I decided to warn Ferris, so that evening I met the Lakeshore Limited. I tried to get to him, but before I could he hurried into a taxi. I grabbed the first empty cab I could find and went to the Barrett Hotel. Ferris had already registered and was disappearing into an elevator. I ran across the lobby, and the door closed and Ferris was gone. I got his room number, 708. Took an elevator. We were just passing the fifth floor when... Those were shots. And they came from the seventh floor. I missed my guess. I didn't miss it because on the seventh floor... All right. All right. Back to your rooms. Come on, everybody. Come on. You too. You're the house detective. Yeah, who are you? My name's Dan Holliday. Did those shots come from this room? Yes, they did. Dobbs. Hello, Dan. What's happened? Look, I'll take care of this. Of course, but the shots came from that room. I know because my room is next door. You? Your next door? Yes. Since I left the university, I've been living here. The house detective will verify that. Sure. Well, that's got nothing to do with this. Why don't you better get inside the room and see what's happened? This is my job. But since you stuck your nose in, stay right with me. Have you got a pass key? Yeah. Hmm. You can still smell the powder from the shots. Yeah. Where's the guy that came in here? Look in the back. Close that door. Now, you two stay right there. I'm going to give this place a look, see? Something fishy here. So your curiosity got the better of you, eh, Dan? Your next door, huh? Yes. Convenient, isn't it? Where's Ferris? He's dead. You shot him, I suppose. I killed him, yes. I saw him get on the elevator and come up here. All right. You saw that. What then? Where is he? I don't get this. There ain't a sign of the guy any place. But there's his hat, top coat, and police on the bed. Which proves he came in here? The bellboy will verify it if he came in here. All right. Let's ask the bellboy. I'm running this until the police get here. Well, by all means, call the police. Dr. Dobbs, would you mind if your room was searched? I was going to suggest it myself. There ain't no fire escape. Nobody fell out the window. And nobody's here. Oh, please, let's look in my room. Then you can question the other guests on this floor. Okay. Come on, you two, out of this room. Well, Dan, what do you think now? I don't know. Maybe I've stopped thinking. Well, the case was a sensational one. Two shots fired. Nobody and no Alexander Ferris. Two days later, Dr. Dobbs visited me in my apartment. Well, Dan, have you made any headway? I'm not trying. Oh, yes, you are. It intrigues you, Dan. It's a hoax. The whole thing is a hoax. Not the whole thing, Dan. I give you my word of honor that I killed Ferris. Will you tell the police that? I already have. I confessed. You what? But they laughed at me. You see, I'm known now as a crank. I confess to all murders. Where is Ferris' body holiday? How did I get it out of the room? You didn't. You couldn't have. The other guests rushed to the doors after the shots. They only stared at me. You couldn't have carried his body without being seen. And the bellboy verifies the fact that Ferris entered his room next to mine. And yours was empty. So, what have you got? Dobbs, I don't believe he killed Ferris. Why then where is he? I don't know. So, I fulfilled two of the conditions we talked about our first night. Remember what they were? Yes, the victim had to be a stranger to you and the body had to disappear. And the third condition, I escaped detection and punishment. Dan, why don't you tell the police about me what you know, what I've told you? They wouldn't believe me. No, they wouldn't. But Dan, I swear to you that I killed Ferris. If you figure out how I did it, I'll admit it and take my punishment. I am not the police. No, no, you're not. But you know more about this than they do.  All you have to do is put together the pieces of the puzzle. It's really very simple. Well, goodbye, Dan. Holiday. Mr. Holiday. I'm sorry, Susie. I was daydreaming. About Dr. Dobbs? Dobbs. Gee, I think it's some kind of a joke. There just isn't anybody that they've been looking for almost a week now. That's what bothers me. Ferris is missing. He left his hometown, took the train, came here. I saw him. I saw him. I saw him. I saw him. Then... No Ferris. And the police won't believe Dr. Dobbs. Or me. Kling thinks I'm in the same class as Dobbs. I know. Oh, thanks. It's got to be an answer, though. No one, not even an admitted genius such as Dobbs could kill a man and do away with his body. But there isn't a trace. Look, Dobbs had about 15 seconds to kill Ferris and then hide the body. Yeah. What were you going to say? I'm not sure. Dobbs said I had the whole solution in my head. Susie, ever see a magic act? Magic act? Oh, you mean a magician? Slide of hand? That's right. Slide of hand. Illusions. Now you see it, now you don't.  Keep your eye on the magician and miss how the trick is done. I don't know what you're talking about. I'm not sure. I do, but I've got an idea. Susie, we're going to send a telegram. Where to? To Alexander Ferris's hometown to the chief of police. But that's been done. You know that. Sure, sure I do. But the other telegrams were about and concerning Ferris. Well, what's yours going to be? About a perfect stranger. Well, I was shooting in the dark, but I hit. The answer I received to my telegram made me sure I had the solution to Dr. Dobbs' illusion. Smart police work in Ferris's home town proved it. So that night I went to see Dobbs. It's nice of you to come to see me, Dan. I was wondering if you'd forgotten me. Everyone else seems to have done so. No, you're not forgotten, Dr. Dobbs. Quite the contrary. Oh, how do you mean that? Just the way I said it. May I sit down? Certainly, please do. Thanks. May I offer you a drink? Oh, no, thank you. Mind if I have one? Please do. You come to see me for a very special reason, haven't you? Yes, I have. Read this telegram. It's from the police in Ferris's home town. Huh? Hmm. Did you guess or did they? I did. I'm glad. Glad you were my audience. It was fun playing to you. Yes, you were the magician. I was the kid in the audience with his mouth open and his mind closed. Magician? Not quite. Oh, yes. Like the trick where the magician shows the audience a nice big red ball. He gets them used to seeing it. He conditions them to its size, its shape. Then he covers the ball with a handkerchief. Makes a mystic pass and the ball is gone. Go on. What then? Ah, but the ball never disappears. It never goes under the handkerchief. All the audience sees is a similar shape, outlined under the silk. Yes, I'm very happy I chose you as my audience. I'm not. I don't like to be the one to catch you. Why not? I took the risk. Ferris never came to the city. You got off the lake shore limited that night. And what else, Dan? You called me and told me Ferris would come here. That day in his hometown you pointed him out. You made me take a good look at him about your height and build. I even mentioned that, I think. Yes, you did. Go on. Before he left, you came here.  You took his top coat, hat, and the lease. Then you dressed him in entirely different clothes. Took his body to the freight yards. That telegram from the police there verifies that an unidentified man was found dead. Yes, unidentified, because the police weren't anxious to identify that body. But they did this afternoon. Dental work proves the man to be Ferris. You see, Dobbs, there's always a clue. Always. There is no perfect crime. But just a moment. There were three conditions to the action of committing a perfect murder. Now, I fulfill two. Now, the third. I must escape detection and punishment. How is anyone going to prove what you've just said? By your admissions, Dobbs, the police are in the next room and outside in the hall. They've heard every word. There are still a few things to clean up, but there isn't time, is there? I still have to escape punishment. I'm sorry, but you can't. Okay, boys, come on in. Well, well, the police. But, Dan, I still say I've fulfilled the last condition to escape punishment. It's a good thing you didn't take the drink I offered you. I knew as soon as you came in that you had me. Dan, explain how I did it. It's no fun doing something clever if no one appreciates it. Dobbs, Dr. Dobbs. So long, Dan. Don't forget to explain the rest. It's been a wonderful chess game. Now, checkmate. What did he kill Mr. Ferris in the hotel? I told him. He didn't, Susie. He killed Ferris in the man's own hometown. You see, I thought I'd followed Ferris to the hotel from the station, but I had followed Dobbs. And then? Very simple. Dobbs had reserved a room next to Ferris's. Then disguised as Ferris, he went into the room Ferris had reserved. Dobbs took off the top coat, had put the police on the bed, fired two shots, blanks, then stepped quickly into his own room. Do you see? Oh, sure. Leaving the other room empty. Right. So everyone was looking in the wrong place for Ferris. Everyone assumed he'd really come to this city, like the old trick with the ball, Susie. You think you see it, but you don't. So you look in the wrong place. Gee. He was really smart, wasn't he? Susie just remembered this.  Everyone makes mistakes. But Dr. Dobbs didn't. Oh, yes, he did. He made the same mistake I did. He looked in the wrong place. What do you mean? You see, I had to trap him into a confession. He assumed that dental work would identify Ferris's body, but the man found in the freight yards had perfect teeth and no dental work. Good night, Susie. Listen in again next week when, through the courtesy of Paramount Pictures, Alan Ladd stars as Dan Holiday in Box 13. Box 13 is directed by Richard Sandville, and this week's original story was written by Russell Hughes. Original music is composed and conducted by Rudy Schrager, and the part of Susie is played by Sylvia Picker. Byrne Carstensen is in charge of production. Box 13 is a Mayfair production from Hollywood. Watch for Alan Ladd in his latest Paramount Picture.


Hello My name is Carol Sopcac and this is Yeah, I'm Michael McKeon. I'm a software developer Red Hat And I'm a software developer at Starburst and actually one of the co-founders of the company I'm also The presto committer and today we will talk about presto And also about Kubernetes and how these two played together So what is presto exactly so presto is an open source community-driven project Which was started by Facebook and Facebook open source it in 2013 and from from that time It the community grew on the project. There were more committers more companies involved into the project So it's quite large at this point In the essence presto is a distributed SQL engine There were two goals Driving the presto. So first of all was the scalability and the other one was the performance so because presto was Developed initially at Facebook those two goals were Like the main motive of creating the presto. So the presto was tested for those two key aspects Every time during it during it it's lifetime Okay, so The main feature of presto is actually that it separates computation from the storage and this gives you great flexibility For one you can scale compute resources separately from the Storage resources you can have multiple clusters for computations for the other the other important reason factor of this is that Because you separate compute You can also federate data from multiple data sources. So presto can read data from the data sources From multiple data sources like HDFS, but also from distributed storage in the cloud but also from other data sources like Traditional relational databases Another thing is that presto Allows you to not lock in with any specific cloud vendor or vendor at all. So presto is had up distro agnostic It's not tied to any big how do distribution Because it's it supports multiple storages. You also are you are also not locked in within the storage So you can read from S3 Google cloud Google Storage Azure files is Azure Azure storage and so on so If you want to move from one cloud to another presto also is a good choice here because you can have a common Interface to your data independently where your data lives There is a lot of companies that use presto a lot of them are web scale companies Obviously the most famous one is Facebook, but there are also other ones like Linked in Twitter Yahoo Netflix and so on we will get to more details later on When I will describe the scale at which they run presto Let's go briefly about let's describe briefly the presto architecture so Presto is essentially Presto is essentially composed of two components One is the coordinator and the other One is our workers So when the user issues a query he goes he he goes to coordinator with the query request the coordinator then Does the query parsing it optimizes the query? And it also plans the work and schedules the work on the workers The workers are the nodes that do the heavy lifting they read the data from the external data sources And do they do the computations like? Distributed join aggregations Whatever is needed to run the SQL query Right and obviously again, it's important that it can read from multiple data sources Yeah, so why presto is That fast first of all is it's in memory processing engine So no intermediate results are down to any persistent storage and this is one aspect why it's So performant another important factor is that it's columnar processing is based on columnar processing So internal structures within the presto itself store the data in a vectorized format and We are very We put much very great focus to details when tuning or writing Performance critical code like operators So we try to use data structures in such a way that we minimize Garbage collections and ideally presto should never trigger a full gc in Java we also do a lot of Micro benchmarks and macro benchmarks and we so for example when we change some aspect of a Operator like join we really try to make sure it's faster. It doesn't break and actually Right, so we try to assert the quality here Another thing is that we generate runtime in at runtime we generate bytecode for the query execution So for example, if you have an expression in SQL on the or a projection or something like that Then for such things we generate bytecode so that we reduce the interpretation overhead And very important factor is that we have a dedicated Parking and or a series which read directly to internal presto structures And because those file formats are also columnar we get really really good performance here as I mentioned presto can be multiple data sources and This is implemented by a thing called connector. So connector There is a in prayer within presto There is a connector SPI and if you want to implement your own connector You have to implement certain classes center interfaces of that SPI So for example, you have to implement the metadata SPI to tell the presto What tables you have what schemas you have and what are the table layouts? You also can implement the statistics API so presto comes with a advanced cost-based optimizer So that if you provide statistics to the presto it can optimize the query better and make the query run faster Also another SPI that you have to implement actually is the data location SPI Yeah, so you you have to tell the presto where the data lives And workers have to and you have to also implement the data streaming SPI For so that presto actually can read the data from your data source if you do all those things then you have your own connector How you can deploy presto so presto I think the most common now deployment pattern is that you can deploy and presto Separately from the storage and this is becoming more and more important once we move to the cloud This gives a great flexibility of upgrading clusters having clusters for multiple different workloads or Just having cluster per internal user group within the company But historically it is it is still possible to deploy presto to collocate presto with the storage nodes and if you are a larger company like Facebook they even they use even more advanced storage patterns like Mixed so you actually put presto nodes in the same rack as the Data nodes so this is for the really really large clusters on prem clusters So what's the ecosystem of presto First of all the most important connector of presto is the Apache hive connector. So we're using this connector You can have a seamless experience when moving from hive to presto and basically this connector Tries to behave similarly as what as what hive does for this storage Despite its name the connector can actually read metadata from not only hive meta store, but also from glue for example and It can be used to read data from HDFS as free Google cloud storage Azure Blob ADLS gen 1 gen 2 or as free compatible Systems, so anything you want Now it is important to understand that we don't use hive underneath to execute the query. So Press it's the presto engine that's running the queries not hive and that's why we get great performance Apart from the Big data connectors, you can also have connectors to your relational databases. So we to name a few we support mycql PostgreSQL Retchseve SQL server and so on there is large. So Yeah, and we do things like pushdown of filters to the relational databases for example, right? And this will continue to grow as we move forward will push even more stuff to the underlying databases Now we also support a bunch of non-relational data sources like Akumulo Kafka Elastic search name a few so because of this you can have a really Unified view over all of your data within your company over various data sources So this frees you from having to have your own ETL for some cases now even Presto we support we try to be Well, we actually we are actually anti SQL compatible So the whole TPCH TP CDS suits pass. We don't need any hacks there. They just run And we support some advanced SQL features like very complex correlated sub queries or I know some advanced window functions to name a few Now apart from that presto also comes in with the security patterns So for example, I think the most notable feature is the user impersonation So the user that comes to the presto will be the presto will then impersonate that user when talking to external data sources so that you One you have you can preserve your security patterns security enforcement And the other aspect of that is that you can have a auditing for example Another important thing is that and this is actually exclusive to starburst We have a sentry on to ranger support So what ranger gives you is that you can do? column masking or row filtering and this is really this really becomes important once we move to this since we are moving to more restrictive law again law about How you store the data and who can access the data? Now also when logging into presto, you can use various patterns like Kerberos or LDAP or Basic authentication, which is password based. We we are constantly adding new things there Yeah So how do you actually talk to presto? So you can use JDBC open source JDBC driver To New application, but you can also you see lie. There is also an ODBC driver, which is commercial and this is also this is from starburst And yeah So and you can use various tools to Use to query presto. So if you want if you don't want to go if you don't want to write your own query pipe query Pipelines or Like scripts for ETL or something you can use one of the existing tools to for example generate reports Yeah, so the list is quite large here And let's let's go back to the companies that are using presto So the most famous company is obviously Facebook. So they have really huge clusters of presto like 10,000 node plus and they have like hundreds of concurrent queries at the same time So they I think they're they're the biggest user of presto internally Like the bigger user of presto at all and they have like 300 petabyte of data. So it's it's astronomical Our companies that use presto are net net net leaks So they also have a lot of data like 100 petabytes. What's different about them is that they're running presto completely within the cloud And they have something like 300 plus nodes there So uber also uses presto 150 petabyte of data 160,000 of queries per day 2000 nodes plus Twitter also 2000 nodes Comcast 100 nodes. This is actually it's Comcast is actually supported by starburst There is lift so they use it for interactive queries mostly reporting There's yahoo Japan 200 nodes plus also starburst supported Finra Finra is a large u.s. Company that does the financial auditing I think so they Have also 100 plus nodes and they use our support So if you want to join the community You can use that I recommend joining the slack you can learn a lot of interesting things there. We are all there and we try to answer the questions or Travels with the problems. So Yeah, I really recommend that There there is a GitHub presto is available on github You can also for example file an issue there if you find something Interesting. There is a mailing group also Yeah, I would also like to talk a bit about starburst so the company was founded in 2017 and it consisted of About It consisted from Committers the presto project which generated about 50% of commits within the crystal SQL and We come from We have a we come from various companies, but we have experience if All past companies were try data had apt which was the actually first SQL first iteration of the SQL on hadoop engine Vertica and it is a What we do is that we offer presto on various platforms and the platform will least will grow So we offer presto on kubernetes On Azure on AWS gcp and so on and the companies had acquired at quarter earth in Boston now What we contributed to presto or give extra is that we have a mission control around presto So this the presto even Presto is really scalable and really fits the cloud, but there are some details that are very specific to presto. So we try to Lower the bar barrier of entry for the project With mission control, which is the UI of a presto We try to automate the cluster creation and make it easy and this will be this will continue to grow into the integrated presto platform We also add that security integrations for held up ranger Kerberos so a lot of enterprise features around security We constantly improve the SQL of the presto support of the presto. So this constantly improves we add We try we add latest features from the latest SQL standard But we also enhance existing features for example for the correlated queries. We support new use cases We also provide ODBC and JDBC drivers and these are certified with tableau And We apart from that there are connectors, which are star bus specific So if you if you want to integrate oracle if you want to integrate snowflake or Tra data We have connectors for these so that you can have unified view But you can also offload from some of these databases to presto. So migrate from from the stuff And we also The next two things are that we are also constantly improving queer performance So we get the feedback from the users, but we are also doing internal benchmarks and we also there are also Long-term projects within the presto that aim at Making it even faster. So we constantly work on these One another for example of an example of such project was the cost base optimizer So it was star bus that added that And this allowed for the standard if you if you run the TPCS benchmarks with the cost base optimizer you get like Many times. I don't recall the number now But it's like many times the performance of running queries without the cost base optimizer Which translates to lower cost of ownership So if you want to try Starbust you can go to our web page. You can try for example with kubernetes So it's with kubernetes. For example, you can do the you can launch the actual presto cluster in like Five minutes. So this is quite amazing Right. So what I would like to do now is I would like to show you a demo how the presto works Let me switch to the console So what I have here Is I have a pre-existing kubernetes cluster within the ws consisting of Six nodes R4 8x large so quite a beefy ones And I have a presto deployed there. So let's see What kind of pods I do have Okay, so as you can see Oh kubernetes Integration is based on the kubernetes operator. So it's really native kind of to the kubernetes cluster Operator monitors the Presto resource type and will create a cluster If you create a cluster, so let me let me show you that so for example with this one with you can do So So kubernetes operator will monitor resources of type prestos and I Created such resource and kubernetes operator Spound a cluster for me the cluster consists of a coordinator, but also It also consists of five worker nodes Now let's see how the definition of the cluster looks like within the kubernetes So so for example what you can see here So for example, what you can see here is that I Defined Cat connector to the presto SQL instance also in the cloud But apart from that I also have a connector Deployed to hive within the cloud. So there is a hive Metastore EMR instance at this EMR instance contains the tables TPC htpc this tables which are stored on S3 So just those two entries allow me to add connectors for those two very different data sources Okay, so what I will now do now is that I will show you the I will run the CLI of Presto and issue some queries there Right, so I'm so what I did now is I run the pistol I connected to kubernetes To the presto coordinator pot and run a CLI there And what I can do now is that I can do See let's what catalogs I have within presto system So as you can see, I have a hive catalog. I have a possible SQL catalog. I also have a tpc h catalog which is for generating tpc h data on the fly I Can show you what I can so I can this Show the schemas from these catalogs for example, so I can show schemas So as you can see hive catalog contains the tables which we usually use for benchmarking And it contains the tables are for example tpc h of 100 gigabytes of our C type like this one Let's see what schemas I have in postgres So I have information schema usual and the public schema usual postgres schemas Let's see what tables I have in public schemas in public schema in postgres What I did for the demo is that Tpc h data set consists of fact tables, but also from dimensional tables I copied some dimensional tables to the postgres SQL And I will issue a query That spans across that will fetch the That will use them Dimensional tables from the postgres SQL, but also but also use the fact tables from the hive connectors so as you can see I can combine S3 data with the Metadata tables from the classical connectors and this also this this show is the power show with the power of the of presto before I do that I will forward the Presto coordinator UI locally. Okay, so I have it So this is the UI of the presto You see that I have five active running workers. I already issued some queries to presto Let me now Run the query So this is one of the tip CH queries that are used for benchmarking as you can see here I use tables from the fact tables from the from the tip CH From the hive connector, but use the dimensional tables from the postgres SQL connector. So let's run the query Let's issue the query and You will see now so Yeah, it actually finished in 10 seconds, but you can see that it was running for a while and it produced So if you can go to the query details, for example you can see Let's see if it produced a result. It did so here is the result Here are details about the execution how it how it was scheduled how many stages it had This is also the status of the task on the workers So again, it's important to know that presto. It's running its own execution engine. It doesn't It's not just a like Semantic overlay over the existing databases. It just runs the computations in a distributed way. Okay, that's that's everything I had Let me go back to the presentation so So So, thank you again and now We will talk about Operator more. Thanks. So One of the things that I do at red hat is that I work with our partners who are also working with open source to help them To help them bring their technology onto Kubernetes and onto open shift and so Let's talk a little bit about operators and you know how we did this So how many people in here are familiar with kubernetes operators or the operator pattern? I should say All right, so I'll go pretty quick through this since probably most of you already know this and when I get details wrong You can just shout at me and let me know how wrong I have it Okay, so in general and you know, this is kind of how we use kubernetes, right? The user comes up says something like I want a pod kubernetes goes and does a bunch of stuff and returns a pod to them, you know in some manner or fashion and This little circle here is kind of indicating somewhere inside. There's kind of a loop Watching for these things happening updating events as they come in and internally there's these mechanisms You know Xcd is like this storage that we use for all the different, you know Objects that come into the system and that's continually talking to internal machinery and side kubernetes Which again is looking for all these different types of objects So we mentioned a pod before but what I tried to do here was grab like a to z of all the different objects and kubernetes So from API service to volume attachment the internal mechanisms are watching for updates here Sending the updated information that CD returning it back to the user deploying containers or attaching volumes or creating API services Whatever that happens to be So the question comes in How do we extend kubernetes because one of the things that happened very early in kubernetes was that people said well You know pod is great, but what I'd like is a presto and what does that even mean? Well, it's a little bit much for the kubernetes maintainers to add special objects for everything And it would it wouldn't scale well for the project as an open-source project to just let everyone add their stuff in So this operator pattern started to emerge And I think if I'm not mistaken our friends at core or s really pioneered a lot of this and and showed us how to Create this pattern and in the beginning there was you know talking between controllers and operators These were different types of mechanisms internally But the idea was we needed a way to be able to customize these things so How can I capture this in? Side of kubernetes right I want to know one presto might be a presto controller It might be a hive meta store a postgres SQL database to store information. How do I encapsulate this all together? Custom resource definitions these used to be known as extensions inside kubernetes And these give us a way to start defining the data or defining the objects that make up You know one presto for example now the back end of this is there's now an operator kind of looking for these things those loops are now Looking for this special type of resource that I've made I'm just going to highlight a few sections here on this So we can see at the top this is the type of thing that I'm creating inside of kubernetes I'm telling kubernetes Please make a custom resource definition for me and it knows how to watch for these things and in this case I'm telling it what do I want to call that I want to call it a presto And what would I call a list of them and what would I call it in plural and and these things help with the command line Tooling that you have and and how you interact with these things And then lastly you can see down here I can give like a version to what I'm creating and the point is that when I create this resource definition Now kubernetes knows what a presto is. It's not necessarily watching to do anything with it at this point But it knows what it is Now if I would like to make a presto I need to issue a custom resource manifest to kubernetes and this gets pushed in and this is you know This is how we actually deploy a presto. So again, you can see the type here This is what we put in the resource definition yep, and You can see the version number after it and then the rest of the information here is really specific to presto It's telling how how does presto get configured, you know, etc And at this point, you know kubernetes isn't really do anything with this because it doesn't really have any sort of watcher That's looking for a presto type. So the presto operator is now gonna Can watch for these resources as they come in and then it can start to do whatever it needs to do to deploy the workers to deploy the hive metastore, etc so Getting started building operators is kind of been a long time coming in the community and what I wanted to do here Was share some resources and talk about some of the ways that you could get started writing your own operator One of the biggest places I think to go is the operator SDK This is at github in the operator framework I guess group and there's lots of different projects in there And you can write these operators and go ansible or helm and then what they have is a tooling that will create a Framework for you So you really have all the pieces necessary To attach to kubernetes to put your custom resource definition in and then to watch for when those resources come in So you'll have you know a code point that you can just start putting in your own custom things Another option is kube builder. This is popular in the upstream kubernetes community And I personally have not used it very deeply so I don't know a lot about it But you know I from what I've heard is it's another way to create these things Another one that I'm familiar with if you're into more JVM based languages is the the ab the JVM abstract operator The author of which Yerka Kremser over here Has kindly put into github and we've seen like Many different JVM language operators come out of that so you could write it in Java you could write it in Scala The list is is pretty large anything that you can compile in a JVM you could make work with this And lastly if you're if you're really excited about this and you just love to hack on kubernetes You could roll your own And there's a whole list of client libraries for many different languages And what you'll learn about during that process is how do I register my custom resource definition? How do I create a watch that looks for updates to that definition? You know you'll see how these things happen, but You also won't be taking advantage of the engineering that's gone into these other projects So you'll have to do all of your own, you know security testing and you know find your own bugs and all that exciting stuff that we love about software development So the next part is okay. I've created an operator. How do I get it into kubernetes? How do I let kubernetes know that my operator is looking for a certain type of resource? well One thing you could do is just manually insert it these operators running containers they running containers in kubernetes and Depending on your kubernetes, they might need a little special permission to be able to you know inject custom resource definitions But when I'm testing these things I run them on my laptop and just connect them to a remote cluster That's not going to scale very well in production. So there's a project called the operator life cycle manager and This is another operator of its own that can help you to Package your operators to get them injected into kubernetes and it's got a whole life cycle around keeping your your operator up and running And it'll you can encode the dependencies that your operator needs There's a way to discover operators in the olm So if users are looking for a presto they can search the operator hub for for a presto and then hey There's an operator for this You can also get automatic updates by subscribing to channels through the olm and then it will upgrade your operators on your cluster And if you want to know more I'd say go to operator hub.io. There's tons of operators there community operators And you can just kind of explore Now what I'm going to show you here is So the kubernetes that I use most frequently is open shift and what we're looking at here is just a screenshot I took of the open shift container platform But if you are an administrator You can see over on the the left hand side I've got this operator hub open and these operators are ready to be deployed directly from the console So I could just log in I could say all right. You can see there's a big data Section there. I go to big data look for presto. I click install it and now I'm ready to start deploying prestos on My kubernetes cluster right so I can start playing with this technology, you know right away So the next part of this is like you've created your operator. You've got the olm managing it You understand, you know, how it works. You fixed all the bugs. How do we publish this? How do I get my operator into the operator hub so that people can Search for it and then be installing prestos in no time, right? So, you know a couple different questions, you know, you first have to ask yourself Are you gonna make an open source or a closed source driver or a closed source operator? You know, how will you manage those things? I won't get too much into that I mean, obviously I'm gonna advocate for an open source driver But you the point here is that if you are in an organization Where you are creating closed source code or you're not able to share your code There is not a requirement that your operator be open source. You could create a closed source operator and run that The other thing you'll want to do is start automating your image builds So as you every time you update your operator every time you're testing You know you are doing testing right every time you're testing passes You're creating new images and automatically uploading them again Continuous testing this is where things get difficult, you know, because you can imagine for something like presto You saw that it deployed a lot of pods with it and there was a lot going on there, right? So sometimes testing can be really difficult in this respect because you could do unit testing just for the small pieces You know if I asked for a presto does it actually make the pods that I think it should But then the next part is how do I test to make sure that the presto it deployed works? That's very specific to your organization and to the code that you're creating because you might need to you might need to Have data to query you have to have something that injects the queries, you know, so You can see this is where things get complicated But then the last part is you can upload your operator Information to the operator hub and this is where the tool this is why I kind of led with operator SDK Because the tooling and operator SDK will create the files necessary for you to make it really easy Just to upload those and you have a definition file. That's this cluster service version that will describe You know what your operator is where the image comes from, you know some bits and pieces of how you could search for it I think maybe you can encode like an image in there, too. Like so it shows the icon for your project now Just to talk a little bit about the tooling that we use When you're testing an operator, you may not necessarily want to deploy your own, you know Kubernetes to AWS or something like that So I just wanted to highlight some of these tools because these are things that you could run on a by today's standards modest laptop 16 gigs depending on you know VRAM depending on how complex your Your deployments are you could run these on you on your laptop So there's mini cube, which is you know, very popular. It uses virtual machines to spawn up Kubernetes on your machine There's another project called kind which is Kubernetes in Docker So you can use if you just have Docker on your machine You can use kind to deploy Kubernetes as containers and then you know you can interact with Kubernetes that way Excuse me and then The last one that I'm highlighting here is code ready containers And this is a project from in my mind just some absolutely brilliant engineers who have taken all the tooling that goes with OpenShift and put it together as an installer that can create an OpenShift instance on your laptop and OpenShift is a little different in some ways from Kubernetes in that it It has a lot more like health and autoscaling kind of built into it So that it needs a little more robust deployment You know to really get the most out of it and this and code-rending containers has been a wonderful way for me to kind of interact with that So if you're really curious about Kubernetes operators and you want to learn more like this little This this little appetizer was not enough. There's actually a workshop in a couple hours Go learn how to make an operator. They'll get you up and running and you can really you know get into it And figure out how to do this I'll leave this up for a second.  The first one is kind of the chorus Discussion of operators and kind of the philosophy behind the operator pattern and you know There there isn't like an API necessarily for operators, but you know you can learn about how they work The next one is the operator the operator framework and the operator SDK You know, this is where you go to get all that tooling the kube builder book operator hub the JVM operators and lastly some client libraries so Carol, I think like join me again or Carl. Sorry The the point here is that Starburst and Red Hat are both hiring. Yes So maybe I would like to like if you would like to work on exciting project We have a lot of opportunities So we are building we will be building platform and modern platform based on Kubernetes the For the sauce we are also have positions for work for the Presto project itself Yeah, so we really have top people in the company and We have offices in Warsaw. We have offices. We have office in Boston. We have also office in California so, yeah, so We are hiring and If you want I Recommend what one one more thing is that we recently got I think one of the biggest a round ever So for the for the big data company, so yeah, so if that might be also a recommendation I think it's it's it's worth to mention So yeah, and with that we say thank you and I guess we have some time for questions any questions So the question is can presto be used as a way to migrate from Oracle to other databases and you know what? I think Karl knows the answer to that From Oracle to Presto or from Oracle to something else Yeah, I mean as long as there are connectors you can migrate your data from Oracle to something else and you can also Have a consistent view during the process for example, right? So we can have some tables here some tables there We've seen cases Actually for the for the big data data for big data where big data days of databases are being migrated from so for example, we've seen Customers migrating from tra data, for example, they want to offload their data from tra data to presto Yeah, so this is one of the patterns that we observe Yeah, so the question was what is the difference between between StarBros distribution and open source distribution? so I think I Think some of the key aspects are that we provide this ranger and security extensions which are enterprise components and Those are often enablers for the customers to use presto at all Another thing is that so with ranger for example, we Can be a drop-in replacement for existing hive Hive also uses ranger But if you if you use ranger with presto and hive connector, then you can enforce the same security policies apart from that we give you the QALT connectors so like Oracle connector There are also connectors for the other databases like Tara data like snowflake This is another aspect another thing is that we We also have Some performance improvements, so for a long time CBO was On only within like it was first in our starburst release and then only it landed in presto SQL open source and We also give you the vehicles to deploy presto right so you can deploy presto Using Kubernetes, but you can also deploy presto on AWS with the cloud watch cloud Formation templates, so we also give you this Seamless experience and this will continue to be more important as we go forward so we will I Make more around presto so that like you won't need to set up ranger yourself But for example, we will have policy engine or self integrated so that's even more That's this lowers the barrier even more for for customers and Another thing is that we provide the support for you and this is often very important to have a supported solution So yeah, the question the question is in the context of the operator on Kubernetes What is actually doing the work to spawn and scale out? Is it the operator or is it actually presto so? So it's kind of mixed because if you scale down for example, you don't want to terminate existing queries so we have an integration with presto itself, so we do kind of graceful scale down and This integration like another aspect is that we do auto configuration within presto So when the pot is started, we try to set up properties of the presto so that it matches the pot capacity like memory or CPUs Yeah, and operator also translates Like the spec properties From the operator to the presto kind of properties, so it provides a nice front end of our presto I expect that there will be even more tighter integration in the future between presto and operator so that We are Planning to support things like blue green blue green deployments or auto scaling and then There will be a part that presto would need to be adjusted or extended for the custom scheduler Or custom auto scaler that would trigger some actions around that like tell if I need some more nodes or not like maybe Maybe there will be some required Things around the query dispatching if you have multiple clusters, right? So this will be more tightly coupled in the future Thank you


What is the difference between Algebraic, Long Division and Synthetic Long Division? Synthetic Long Division is just a quicker way of doing this. Here, I'll show you the Synthetic Long Division, right? Check this out. Yo! First time chat. Lich! Druggan. How are you doing? I'll tune in more often. Goodbye. Goodbye. Sweet dreams, Ozzy. Take a look at the Synthetic Long Division. We'll do the same guy. I'm going to erase these guys. This is what we got with the Long Division, right? Here's what we can get with Synthetic Long Division. Want to become famous but I don't want to fly. Followers and viewers. Not really. First time chat. Jala. I have no idea what you're doing right now, but I know some math thing that might be very, very useful. I will type it in next message, okay? Hello, I'm a snake. How are you doing? Hello. Good to see you again. Which math subject should I learn to teach high school math, aside from algebra and trigonometry? Which math subjects should I learn to teach high school math? To teach high school math, you need to learn everything. So yeah, you would have to learn everything. But I would say start off with the basics first. Learn how to deal with fractions right away, ratios right away, factor polynomials. How to move around an equal sign right away, powers and all that stuff really well. That's where a lot of people have problems with initially, right? And then you've got to get into functions, graphing and stuff like that. But let's assume we wanted to do this. We wanted to do Synthetic Division on this, right? X squared plus 5x minus 7 divided by x plus 1. So what you do, you do this.  And you're going to do it this way. And you're going to take x plus 1, and you're going to set it equal to 0 because you're assuming that might be a factor of that. And you're going to write this as x is equal to negative 1. So what you're going to do is, you're going to go x is negative 1, you're going to divide it into that. So what you're really doing is, you're subbing in, x is equal to negative 1 for x, and you're trying to find out what the remainder is. The remainder is 0, that's the remainder theorem just telling you that you're on the x-intercept. In this case, if it happens to be negative 11, that means if you sub in x is equal to 1 into this polynomial, your y is negative 11. It's a point that you just got. I'll show you how that works, right? So the way you do synthetic division, your first order is to bring this guy down, and you multiply this by this. One times negative 1 is negative 1. Add these guys up, you get 4. Bring this guy here, multiply by negative 1, becomes negative 4. Add these guys up, you get negative 11. What you have now is, this is this, 1x plus 4. So you took an x squared and divided by an x, your result is going to be 1 less x. So this part becomes x plus 4, which is that guy there.  So what this really means is, if you have this polynomial function f of x is equal to x squared plus 5x minus 7, if you find f of negative 1, basically sub in negative 1 for x, you're going to get negative 1 squared plus 5 times negative 1 minus 7. This is going to be 1 minus 5 minus 7, which is going to be 1 minus 5 is negative 4 plus negative 7 is negative 11. So you just went, f of negative 1 is equal to negative 11. So on a grid, negative 1 and negative 11 is a point on this grid.  So it's going to be looking, it's going to be like this or like that. What's the y? Just have this negative 7. Here's negative 7, 0 and negative 7. So the graph looks like this. I don't know where the vertex is. I would have to complete in the square to find the vertex on it.


All right, quickly, let's jump to Musk and Twitter. As you know, Musk is trying to establish new guidelines, moderating guidelines for Twitter, deciding who can be on the platform, who should not, what kind of speech is allowed, what kind of speech is not. Some kind of moderation has to happen. Even having a moderation policy that says any legal speech is allowed is still a moderation policy. So some kind of policy needs to exist. My complaints about Twitter have focused on the fact that their policies have not been particularly objective and not being predictable, have not been knowable in advance.  They get to decide on the rules for what speech is acceptable and what is not on their platform, this is private property. What I would like as a user, as a content creator, as somebody who participates in this, I would like those guidelines to be objective, to be not knowable in advance. I'd like them to know, whoops, I shouldn't say this because I'm at geek.off or I'm gonna say it anyway or just I know, I know, you can't swear but you can be a communist, you can be a fascist, you can be a communist, you can be a communist, you can be a fascist, whatever, just let me know what are the standards and I'll either accept them or I'll leave the platform. And the problem is with all these platforms, including Twitter, there has been no objective standard. David Arsenal, thank you for the support, really, really appreciate it. There be no objective standards. The standards have been seemingly arbitrary. The standards have been you know, biased, clearly biased towards, you know, so some people in a sense inciting violence or presenting a bad perspective views of the world or particularly violent views or particularly just hate speech. But some, if they do it from a certain political perspective, Twitter has been lenient about and has been fine and no problem, you can keep doing it. For example, maybe Islamists talking on there or certain parts of the left, that's been fine but people on the right who have engaged in hate speech, they've been stopped, they've been limited much faster than it seems to be true on the left. So for example, you can get hate speech out of Iran which is fine to put on Twitter but hate speech by individuals who in America is not acceptable, all kinds of standards where you just don't know, you have no clue but there's clear bias, but there's clear bias but it's not objective no matter what. Well, part of the hope was that Elon Musk would bring some objectivity to this, would enforce some new standards, more objective standards, standards that made some sense and were predictable that Elon Musk would also take away some of the bias, eliminates some of the bias against let's say, the so-called right versus the left. And early on, Musk talked about having some kind of committee that would establish these kind of standards that would determine what is acceptable and was not and this committee would make these decisions and the committee would be balanced and there'd be people from different parts of it.  Unfortunately, Musk is a banded objectivity just like it seems like every other platform has made his platform no different than any other platform. He has presented and reported no new standards. I don't know where this moderation committee is. I haven't seen anything new coming out of Twitter to give us some guidance of what is okay and what is not. But what have we seen? We've seen Elon Musk conduct a poll on whether Trump should be allowed on Twitter or not, back on Twitter or not. A poll, we decide these things based on majorities, we decide these things based on how many people voted on an arbitrary random Twitter poll. Really? That's how we make decisions? The poll was I think 52 to 48 for allowing Trump back on the platform and therefore he won the poll. So Trump was allowed back on Twitter. And you could say, okay, the new standard is polls. We're gonna poll everything. But people asked Elon Musk, well, what about Alex Jones? You can have a poll with allowing Alex Jones back on Twitter or not. And if you allow Trump, why aren't you allowing Alex Jones? And basically, Elon Musk said something like, well, Alex Jones hoots children and have a soft search of children. So Alex Jones is banned and Trump is not. In other words, you know, I don't like Alex Jones. He upsets me. I feel bad. And therefore, you know, I'm not.  So just say that the moderating standards, the moderation standards at Twitter now are Elon Musk's whims. Elon Musk's whims.  We have less guidance and less standards right now than we had before Elon Musk took over. Instead of bringing us objectivity, what we now have is try to predict what Elon likes and what Elon doesn't like. Try to predict which threads on Twitter Elon follows and which threads on Twitter Elon doesn't. I suspect that I can pretty much say anything I want on Twitter because I doubt Elon Musk reads my tweets.   Give us objective standards. Give us standards that we can live by. Give us standards that we can understand whether I agree with those standards or not. It will enhance Twitter dramatically just to know what's acceptable and what's not. And if you ban too much content then people will leave Twitter and we'll be back to let's compete which is my view of social media. Anyway, let competition go. Let's do it, let's do it. Let's see which platform attracts the most users. Therefore provides the most value. All right, so that's Twitter. I really hope Musk gets his act together. I don't want to say too much about Twitter because I think a lot is going on. A lot is going on in the background. A lot is going on in terms of hiring and firing. A lot is going on in new features and trying to embed those. I don't want to judge Elon Musk's efforts in totality yet. I think there's still weeks and maybe months to go before we can do that. But on this issue about what is allowed and what is not he clearly has failed and so far. And I hope he gets his act together. I hope so. Thank you for listening or watching the Iran book show. If you'd like to support the show we make it as easy as possible for you to trade with me. You get value from listening. You get value from watching. Show your appreciation. You can do that by going to www.uranbrookshow.com slash support by going to Patreon, subscribe star locals and just making a appropriate contribution on any one of those channels. Also, if you'd like to see the Iran book show grow please consider sharing our content and of course subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who already supporters of the show thank you. I very much appreciate it.