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jemch · 4 years ago

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How It’s Made Index（S11~S20）

How It’s Made是由 Discovery Channel 制作一款王牌节目，又被翻译为制造的原理或造物小百科，本片从2001年推出至今，涵盖了几乎所有的制造技术，非常适合机械专业和对此感兴趣的同学。希望大家享受这趟制造的艺术之旅！

第十一季推出时间为2008-09-10至2008-12-03

S11E01 Binoculars; Sparklers; Rubber Boots; Circular Saw Blades 望远镜，焰火，长统水靴，圆锯锯片

本集看点：光学镜头的精密组装制程，AR镀膜制程；

S11E02 Anatomical Models; Jukeboxes; Tortilla Chips; Spark Plugs 解剖学模型，自动点唱机，墨西哥玉米片，火花塞

S11E03 Pencils; Metal Recycling; Coffee 铅笔，金属回收，咖啡

S11E04 Javelins; Cuckoo Clocks; Hearts of Palm; Windshield Wipers 标枪，布谷鸟钟，棕榈芯，雨刷

S11E05 Technical Glass; Washing Machines; Playing Cards; Crossbows 工业玻璃，洗衣机，扑克牌，弩

本集看点：玻璃镜片的模具加工制程；

S11E06 Cine Cameras; Glass Christmas Ornaments; Giant Tires 电影摄影机，圣诞节玻璃装饰品，巨型轮胎

S11E07 Microphones; Hot Tubs; Artificial Turf; Beer Steins 麦克风，按摩缸，人工草坪，啤酒杯

S11E08 Hot Rods; Decorative Eggs; Fire Hose Nozzles; Baseballs 改装车，装饰蛋，灭火水龙带喷嘴，棒球

S11E09 Accordions; Pineapples; Artificial Joints 手风琴，菠萝，人工关节

S11E10 Giant Valves; Sardines; Barographs; Disposable Diapers 巨型阀门，沙丁鱼罐头，气压计，一次性尿片

S11E11 Heated Skate Blades; Gliders; Hand Bells; Fire Hoses 加热式冰靴，滑翔机，手摇铃铛，灭火水龙带

S11E12 Induction Cooktops; Truck Scales; Tetra Pak Containers; Harmonicas 电磁炉，车重地衡，利乐包装盒，口琴

S11E13 Baseball Gloves; Medical Electrodes; Stetson Hats 棒球手套，医疗电极，牛仔帽

本季资源链接：

magnet:?xt=urn:btih:d779bce9b74c0b6e06c209442fe6d2bd0577fd92&dn

第十二季推出时间为2008-09-10至2008-12-03

S12E01 Pneumatic Impact Wrenches; Cultured Marble Sinks; Plantain Chips; NASCAR Stock Cars 气动扳手，人造大理石水池，炸香蕉片，纳斯卡赛车

S12E02 Jaws of Life; Artificial Christmas Trees; Soda Crackers; Ratchets 救生钳，人造圣诞树，苏打饼干，棘轮扳手

S12E03 Thermometers; Produce Scales; Aircraft Painting; Luxury Chocolates 温度计，挂秤，飞机机身彩绘，高档巧克力

S12E04 Carburetors; Air Conditioners; Sugar 气化器，空调机，糖

S12E05 Combination Wrenches; Deli Meats; Golf Carts; Airships 组合扳手，香肠，高尔夫球车，飞艇

S12E06 Carbon Fibre Car Parts; Hand Dryers; Recycled Polyester Yarn; Fleece 碳纤维汽车零件，手烘干机，回收聚酯制丝线，羊毛布料

S12E07 Police Badges; Muffins; Car Washes; Pressure Gauges 警徽，松饼，洗车房，压力表

S12E08 Metal Detectors; Rum; Tiffany Reproductions; Aircraft Engines 金属探测器，兰姆酒�� 蒂凡尼灯具，飞机引擎

S12E09 Riding Mowers; Popcorn; Adjustable Beds; Cultured Diamonds 乘骑式割草机，爆米花，可调床垫，人造钻石

S12E10 Airstream Trailers; Horseradish; Industrial Steam Boilers; Deodorant 流线型拖车，辣根，工业蒸汽锅炉，防臭剂

S12E11 Screwdrivers; Compact Track Loaders; Physician Scales; Carbon Fibre Bats 螺丝刀，链带式装卸机，体重秤，碳纤维棒球棒

S12E12 Escalators; Kevlar Canoes; Goat Cheese; Disc Music Boxes 自动扶梯，凯夫拉尔独木舟，羊奶酪，碟式音乐盒

S12E13 Motorcycle Engines; Glass Enamel Sculptures; Hand-Made Paper; Vaulting Poles 摩托车引擎，玻璃搪瓷雕刻，手工纸，撑竿

本季资源链接：

magnet:?xt=urn:btih:f97da4fb8bfc1cf29bb923ad6dd2eaff6b522c9d&dn

第十三季推出时间为2009-05-01至2009-07-24

S13E01 Hammers; Swiss Cheese; Roller Skates; Coloured Pencils 锤子，瑞士奶酪，旱冰鞋，彩色铅笔

S13E02 Carbon Fiber Bicycles; Blood Products; Forged Chandeliers; Ballpoint Pens 碳纤维自行车，血液制品，锻造吊灯，圆珠笔

本集看点：如何用碳纤维制作自行车支架；

S13E03 Swiss Army Knives; Player Piano Rolls; Oil Tankers; Racing Wheels 瑞士军刀，钢琴演奏器，油轮，赛车轮毂

本集看点：真瑞士军刀！

S13E04 Bowling Balls; Barber Poles; Felt; Radar Guns 保龄球，旋转彩柱，毛毡，雷达测速枪

S13E05 Pipe Fittings; Music Boxes; Pepper Mills; Hot Rod Steering Columns 铜管件，圆柱音乐盒，胡椒磨，汽车方向柱

S13E06 Gears; Leather Watchbands; Vitrelle Dishes; Kitchen Shears 齿轮，真皮表带，抗摔玻璃碗碟，厨用剪刀

本集看点：齿轮插齿和滚齿制程；

S13E07 Pressure Cookers; Mechanical Singing Birds; Oceanographic Buoys; Tank Trailers 高压锅，唱歌机械鸟，浮标，不锈钢罐拖车

S13E08 Aluminum Boats; Alpine Horns; Luxury Watches 铝壳船，高山牛角，豪华手表

S13E09 ATVs; Alpine Skis; Laser Cutters; Marble Sculptures 全地形车，高山滑雪板，激光切割机，大理石雕塑

S13E10 Socket Sets; Leather Shoes; Aluminum Water Bottles; Bike Chains 套筒扳手，皮鞋，铝制水瓶，自行车链��

S13E11 Carved Wood Sculptures; Flatware; Cow Bells; Fountain Pens 木雕，餐具，牛铃，钢笔

S13E12 Olive Oil; Lift Trucks; Seamless Rolled Rings; Ski Boots 橄榄油，叉车，无缝环件，滑雪靴

S13E13 Cookware; Inlaid Boxes; High-Efficiency Water Heaters; Vespa Scooters 专业炊具，豪华镶嵌盒，高效率热水器，电动车

本季资源链接：

magnet:?xt=urn:btih:b164e21986d83657baf215347cf40ae2c33ed64a&dn

第十四季推出时间为2009-09-18至2010-01-08

S14E01 Mini GP Motorcycles; Fig Cookies; Tool Boxes; Pipe Bends 迷你锦标赛摩托车，无花果曲奇饼，工具箱，弯头

S14E02 Revolver Replicas; Arc Trainers; Oil Furnaces; Vegetable Peelers; Pizza Cutters 西部左轮手枪复制品，健身椭圆机，废油燃烧器，削皮器和薄饼切削刀

S14E03 Metal Golf Clubs; Waffles; Custom Wires and Cables Train Wheels; 金属高尔夫球杆，华夫烘饼，订制线缆，火车轮子

本集看点：热锻成型工艺；

S14E04 Sails; Walnuts; Wheel Immobilizers; Honeycomb Structural Panels 风帆，核桃，轮胎防盗器，蜂窝结构板

S14E05 Surfboards; Stickers; Sandwich Cookies; Concrete Roofing Tiles 冲浪板，贴纸，夹芯饼干，混凝土瓦

S14E06 Ski Goggles; Tower Cranes; Porcelain Figurines; Diesel Engines 滑雪风镜，塔吊，瓷小雕像，柴油引擎

本集看点：塔吊是如何长高的；

S14E07 Stuffed Olives; Astrolabes; Western Saddles 酿水榄，星盘，西部马鞍

S14E08 Custom Running Shoes; Axes; Racing Karts; Animatronics 订制跑鞋，斧头，卡丁车，电子动画

S14E09 Headphones; Diving Regulators; Reflector Light Bulbs 耳机，潜水呼吸调节器，聚光灯泡

S14E10 Fly Fishing Reels; House Paint; Weaving Looms; Ice Makers 飞钓卷筒，房屋涂料，编织机，制冰机

S14E11 Graphite Pencil Leads; Clarinets; Special Effects; 石墨铅笔芯，单簧管，特技效果

S14E12 Air Boats; Onions; 3D Metal Printing; Curved Cabinet Doors 空气船，洋葱，三维金属打印，弧形木柜门

本集看点：金属的3D打印制程；

S14E13 Retractable Ballpoint Pens; Solar Salt; Tubas; 圆珠笔，日晒盐，大号

本季资源链接：

magnet:?xt=urn:btih:5101c33367df80cb2ba1566fc8f467dbcde21af5&dn

第十五季推出时间为2010-04-02至2010-06-18

S15E01 Kelp Caviar; Luxury Sailboats; Dental Crowns; High-Performance Engines 海带鱼子酱，豪华帆船，人造牙冠，发动机

S15E02 Leather Briefcases; Crop Dusters; Corn Whiskey; Drag Racing Clutches 真皮公文包，喷洒农药飞机，玉米威士忌，直线竞速赛车离合器

S15E03 Train Rails; Desalinated Water; Racing Wheelchairs; Parquetry 火车钢轨，淡化水，竞速轮椅，拼花木地板

S15E04 Flight Simulators; Bookbinding; Greenhouse Tomatoes; Hurricane-Proof Shutters 飞行模拟器，传统装订，温室西红柿，防风百叶窗

S15E05 Worcestershire Sauce; Lawn Bowls; Radio-Controlled Model Jets; 辣酱油，草地滚球，遥控模型喷气机

S15E06 Pipes; Rock Climbing Gear; Leather Bike Saddles; Luxury Sports Cars 烟斗，攀岩丝扣锁，自行车座，豪华跑车

S15E07 Replica Foods; Traffic Cone Dispensers; Rocking Horses; London Taxis 食品模型，交通安全锥，摇马，伦敦出租车

S15E08 Miniature Furniture; Garden Steam Locomotives; Hovercraft; Folding Bicycles 迷你家具，庭院蒸汽机车，气垫船，折迭自行车

S15E09 Crosscut Saws; Haggis; Collectible Firearms; 横割锯，肉馅羊肚，收藏枪支

S15E10 Alligator Bags; Lockers; Bench Planes; Deployable Flight Recorders 鳄鱼手袋，储物柜，木工台刨，飞行纪录仪

S15E11 Grapples; Flavorings; Dog Sleds; Athletic Shoes 抓斗，调味品，狗雪撬，运动鞋

S15E12 Retractile Cords; Wood Frame Sports Cars; Sushi 伸缩绳，木结构跑车，寿司

S15E13 Leather Wallets; French Horns; Soy Sauce; Children's Ride-On Cars 真皮钱包，圆号，酱油，儿童骑乘汽车

本季资源链接：

magnet:?xt=urn:btih:f6b32d4b2d935fa1a9af9d02b026367bca667ce5&dn

第十六季推出时间为2010-10-01至 2010-12-24

S16E01 Millefiori Glass Paperweights; Road Salt; Nutcrackers; Car Doors 千花玻璃纸镇，道路除冰盐，胡桃夹子，汽车门

S16E02 Straight Razors; Black Pudding; Steering Wheels; Inorganic Pigments 直剃须刀，黑香肠，方向盘，无机颜料

S16E03 Cast Iron Cookware; Biodiesel; Clothing Hangers; Stone Wool Insulation 铸铁炊具，生物柴油，衣架，石棉

本集看点：连续铸造制程；

S16E04 Needles & Pins; Architectural Mouldings; Locomotives; Clothespins 针，建筑木线条，机车，衣夹

本集看点：针尖的抛光制程，针孔的冲压制程；

S16E05 Filigree Glass; Fish Food; Motor Homes 掐丝玻璃，鱼饲料，房车

S16E06 Surgical Instruments; Ketchup; Double-Decker Buses; Walking Sticks 手术器械，番茄酱，手杖

S16E07 Audio Tubes; Light Bars; Model Aircraft; Snare Drums 音频真空管，灯条，木制模型飞机，金属小鼓

S16E08 Kitchen Accessories; Central Vacuums; Paper-Maché Animals; Hydraulic Cylinders 厨房配件，中央吸尘器，纸型动物，液压缸

S16E09 Liquor Jugs; Deli Meats; NASCAR Engines 粘土酒壶，家禽熟肉制品，NASCAR发动机

S16E10 Digital Dentistry; Nail Clippers; Poster Restoration; Canola Oil 数字牙科，海报恢复，菜籽油

S16E11 Dial Thermometers; Hummus; Spent Fuel Containers; Straw Sombreros 温度计，豆泥，燃料容器，秸秆宽边帽

S16E12 Tequila; Water Beds; Flip Flops; Silver 龙舌兰酒，水床，人字拖，银子

S16E13 Composite Propane Cylinders; Salsa; Water-pumping Windmills; Dragsters 复合丙烷缸，辣调味汁，抽水风车，高速赛车

本集看点：玻璃纤维制作的罐子；

本季资源链接：

magnet:?xt=urn:btih:4fc2ea711b18dc3079a0cdb65688b59f2cf1317f&dn

第十七季推出时间为2011-04-08至 2011-06-24

S17E01 Decorative Sombreros; Salad Dressings; Cap Guns; Regenerative Medicine 装饰戴草帽，沙拉酱和腌泡汁，帽枪，再生医学

S17E02 Cheese Graters; Hot Sauce; Silver Jewelery; Traditional Mexican Chairs 芝士刨，辣酱，银首饰，传统墨西哥椅

S17E03 Game calls; Mayonnaise; Traditional Razor Blades; Butterfly Safety Razors 哨，蛋黄酱，传统剃须刀片，蝴蝶安全剃刀

S17E04 Corn Tortillas; Crankshafts & Camshafts; Bush Planes; Aluminum Bike Wheels 玉米饼，曲轴和凸轮轴，布什飞机，铝自行车轮

S17E05 Folding Kayaks; Pi?atas; Garbage Trucks; Ceramic Composite Brake Discs 折叠皮艇，彩罐，垃圾车，陶瓷复合刹车盘

S17E06 Rolled Wafers; Wood Pellets; Class & Championship Rings; 威化饼，木颗粒，总冠军戒指

S17E07 Speed skates; synthetic rubber; cocoa beans; and bulk chocolate 速度溜冰鞋，可可豆，散装巧克力

S17E08 Custom Steering Wheels; Aerospace Fuel Lines; Apple Pies; Household Radiators 定做方向盘，苹果馅饼，家用散热器

S17E09 Whips; automated pizza makers; incense cones; and scale turbine engines 鞭子，自动比萨饼机，香锥，喷气发动机模型

S17E10 Heather gems; instant film; beet sugar; electric roadsters 希瑟宝石，即时胶片，甜菜糖，电动跑车

S17E11 Underwater robots; lasagne; band saws; and ski trekking poles 水下机器人，烤宽面条，带锯床，登山杖

S17E12 Laminated Wood Beams; Sport Utility Vehicles; Veggie Burgers; Wood-boring Augers 木质横梁，运动型多功能车，素食汉堡，钻木螺旋钻

S17E13 Turbochargers; enchiladas; and watches; 涡轮增压器，辣酱玉米饼馅，手表

本集看点：中空的铸造零件是如何制作的；

本季资源链接：

magnet:?xt=urn:btih:153c8f17185e424a1da8805f16bf13cd9f9d70ad&dn

第十八季推出时间为2011-09-14至 2011-12-06

S18E01 Patterned Glass Panels; Road Cases; Stop-Frame Animation 压花玻璃面板，公路应急箱，定格动画

S18E02 Industrial Wire Ropes; Living Walls; Large Format Cameras; Gemstones 工业钢丝绳，生活墙，大画幅相机，宝石

S18E03 Chocolate Coins; Floor Heating System; Pedal Cars; Latex Swords 巧克力金币，地板采暖系统，踏板汽车，乳胶剑

S18E04 Farmed Caviar; Intake Manifolds; Motorcycle Jackets; Forged Spades 养殖鱼子酱，进气管，机车夹克，铲子和铁锹

S18E05 Wax Figures; Awnings; Sandwich Crackers; Pewter Tankards 蜡像，遮阳篷，三明治饼干，锡制酒杯

S18E06 Cufflinks; Blueberry Turnovers; Dashboards; Pottery 袖扣，蓝莓饼，仪表板，陶器

S18E07 Fish Replicas; Siren Systems; Pre-Packaged Sandwiches; Candlesticks 鱼模型，警报器系统，预包装三明治，烛台

S18E08 Pipe Cleaners; Blue Stilton Cheese; Smart Electric Meters; Telescopes 管道清洁剂，蓝斯蒂尔顿奶酪，智能电表，望远镜

S18E09 Rally Cars; Pork Pies; Floating Fountains; Artificial Stone Ornaments 拉力赛车，猪肉馅饼，浮动喷泉，人造石饰品

S18E10 Tapioca Pudding; Snow Plows; Paddle Boats; Fibre Cement Siding 木薯布丁，除雪车，桨船，纤维水泥墙板

S18E11 Pharmaceutical Blister Packs; Deli Slicers; Oysters; Weathervanes 药品泡罩包装，德利切片机，牡蛎，风向标

S18E12 Top & Bowler Hats; Solar Water Heaters; Sticky Buns; Electrostatic Speakers 圆顶礼帽，太阳能热水器，粘小奶油甜面包，静电式扬声器

S18E13 Turntables; Steam Engines; Playground Equipment; Teflon Pans 唱盘，蒸汽机，运动场设备，不粘锅

本季资源链接：

magnet:?xt=urn:btih:2689e5e93e88a4f1c599bf77f90d3227cebfa7d8&dn

第十九季推出时间为2012-04-19至 2012-06-24

S19E01 Garden Forks; English Toffee; Paint Chip Cards; Bundt Pans 花园艺叉,英式太妃糖，油漆色卡，蛋糕模具

S19E02 Pewter Flasks; Potato Salad; Hydrogen Fuel Cells; Engineered Wood Siding 锡制酒瓶，马铃薯沙拉，氢燃料电池组，工程木板墙

S19E03 Canvas Wall Tents; Peace Pipes; Shredded Wheat Cereal; Cannons 帆布帐篷，印第安式烟斗，块状麦片，加农炮

S19E04 Robotic Hunting Decoys; Canned Tomatoes; Scoreboards; Lassos 捕猎诱饵，罐装番茄酱，电子计分板，捕牛套索

S19E05 Turf Grass; Beef Jerky; Wood Chippers; Bowling Pins 草坪，长条牛肉干，木片切削机，保龄球球瓶

S19E06 Multi-Tools; Jojoba Oil; Marionettes 多用途工具刀，荷荷芭油，提线木偶

S19E07 Fish Decoys; Film Digitization; Cylinder Stoves; Concrete Light Poles 鱼饵，影片数字化存储，筒形火炉，混凝土灯杆

S19E08 Bamboo Bicycles; Chainsaw Art; Breath Mints; Manual Motorcycle Transmissions 竹制自行车，木雕，薄荷糖，变速箱总成

S19E09 Dinnerware; Air Brake Tanks; Frosted Cereal; Fossils 陶瓷餐具，气刹储气罐，麦片，化石

S19E10 Clay; Pitted Prunes; Spurs; Polyurethane Tires 黏土，话梅，马靴，轮胎

S19E11 Tasers; Canned Soup; Jaw Harps; Diving Boards 泰瑟枪，汤品罐头，口弓，跳水板

S19E12 Space Pens; Reef Aquariums; Metal Caskets; Composite Bike Wheels 太空笔，水族馆，金属棺材，复合自行车轮子

S19E13 Navajo Rugs; Crude Oil; Kaleidoscopes; Titanium Dental Implants 纳瓦霍地毯，原油，万花筒，钛牙科植入物

本季资源链接：

magnet:?xt=urn:btih:91bb1169cf63a02a4394608268efd8de9703bdcb&dn

第二十季推出时间为2012-10-25至 2013-01-10

S20E01 Native Healing Drums;Raisins;Stereoscopic Viewers;Ribbon Microphones 印地安疗愈鼓，葡萄干，立体图片观赏器，铝带式麦克风

S20E02 Horse Bits; Oat Cereal; Turquoise Jewelry; Electric Scooters 马衔，燕麦片，土耳其玉首饰，电动滑板车

S20E03 Stagecoaches;Road Reflectors;Fire Baked Pottery;Custom Motorcycle Tanks 驿马车，反光道钉，火烤陶器，订制摩托车油箱

S20E04 Replica Clay Pipes;Drinking Fountains;Orange Liqueur;Compound Bows 复刻陶瓷烟斗，饮水机，柳橙甜酒，复合弓

S20E05 Tissues;Travel Trailers;Slippers;Motorcycle Helmets 面纸，旅行拖车，拖鞋，摩托车安全帽

S20E06 U-Locks; Tepees; Croissants; Rolling Luggage U型锁，圆锥帐篷，可颂面包，滚轮行李箱

S20E07 Prams;Factory-Built Homes;Wood Flutes;Bicycle Tires 婴儿车，组合式房屋，木笛，单车轮胎

S20E08 Thinning Shears;Wagon Wheels;Toaster Pastries;Violin Bows 打薄剪，马车轮，果酱夹心饼，小提琴弓

S20E09 1000th Item: Cycling Shoes;Yurts;Marine Plywood;Oil & Encaustic Paint 自行车卡鞋地，蒙古包，船用合板，油彩和蜡彩

S20E10 Nail Nippers; Jade Putters; Ice Cider; Water Skis 指甲钳，玉石推杆，苹果冰酒，滑水板

S20E11 Paper Fans; Walnut Oil; Copper 纸扇，胡桃油，铜

S20E12 Cast Iron Tubs; Hopi Kachina Dolls; Mine Truck Engine; Memory Cards 铸铁浴缸，霍皮族娃娃，矿场卡车引擎重建，记忆卡

S20E13 Gut Strings;Absinthe;Belt Buckles;Lever Locks 肠弦，苦艾酒，皮带头，杆锁

本季资源链接：

magnet:?xt=urn:btih:3b16e409e27f9101e3d9b5ba17cf000344174c58&dn

#how it's made

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peacehopeandrats · 5 years ago

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Pop Ins

Chapters: 1/1 Fandom: Once Upon a Time (TV) Rating: General Audiences Warnings: No Archive Warnings Apply Relationships: Belle/Rumplestiltskin | Mr. Gold Additional Tags: Fluff, A Monthly Rumbelling (Once Upon a Time), Fun, Travel

Summary: Inspired by the January Monthly Rumbelling. The Golds visit a land where only light magic exists and nine year old Gideon has a rather unexpected adventure.

Notes: This is part of an eventual work in my Growing Up series. Inspired by the Monthly Rumbelling prompt “How on earth did you get up there?” The rest of this story will be included when I get to it, but for now, enjoy this little snippet of life with the Golds, in a realm where only light magic exists.

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Gideon watched his Papa spinning at the wheel and tipped his head curiously as the man's movements created a thick yarn. It looked solid and strong, but there wasn't enough of it to be useful for much of anything. He could imagine it being a pull string for an attic door, or maybe a kind of belt, but that was about all.

“Did you put everything into your boxes?” The words were his mother's. They ricocheted through the almost empty house, making the question seem more mysterious than it was. Packing days always stressed her, but this one seemed different somehow. There was a nervous energy in the air that he couldn't quite understand, not to mention the many whispered conversations between the two in the last week, hushed arguments that stopped the minute he set foot in the room.

Of course, his Papa might have something to do with that. He sat spinning while his mother dashed about, frantically checking corners and closets for forgotten stockings or bars of half-used soap that, for some reason, needed to come with them. This had never happened before. It was why Gideon was so curious about the final product.

“Yes, mother,” Gideon called back, eyes fixated on the movements of his Papa's fingers. He felt spellbound, but in a good way, and reveled in the closeness that came from watching his father work.

“There. Finished.” The wheel creaked to a stop and his Papa held out the yarn. “Go on,” he commanded. “Pull.”

Gideon took hold and gave a gentle tug.

“Ah,” his father croaked playfully, swatting at the air between them. “Give it a real pull. Everything you've got.”

Again Gideon pulled, but this time, with all of his might. The yarn gave ever so slightly, then held. He looked down at the thick fibers in his hands and decided it felt more like a tiny rope than yarn. “What is this for, Papa?”

“I'll show you. Come here,” his papa said. “You're meant to wear it.”

So it was a belt, even if it didn't seem to be a useful one. He moved closer, arms raised, and let his father tie the chord around him, testing the knot with a gentle tug. One end had been left longer than the other, so unbalanced that it nearly dragged at his feet. Both he and his Papa studied the end result, but while Gideon found the new item awkward and clumsy, his father seemed to be fairly pleased.

“Yes. That will do nicely.”

At this, his mother appeared, hands on hips, head tipped to the side. “Are you sure it will be long enough?”

Rumple gestured at the floor. “Do you want the boy to trip himself up every time he takes a step?” Rumple chuckled and patted Gideon on the shoulder. “I think this will be just fine.”

Gideon looked from his mother to his papa and back again, blinking in confusion. “So... why do I have to wear this?”

“Your father and I found a special realm,” his mother explained as she sat in a chair beside the spinning wheel. Light from outside pushed through the window and shone on the streak of gray that had grown in her hair. Gideon's eyes flicked away, unwilling to admit the sign of his mother's mortality, and rested instead on the ring she wore. Reading his action as a need for reassurance, she reached out to take his hands in her own. “It's a place of light magic, where darkness has never been seen... that we know of, anyway. We're going to find out if that's true.”

Gideon felt his eyes go wide with hope and he spun so quickly to face his Papa that he lost his balance and had to be steadied by his mother's quick reflexes. “Do you think they can help?”

His Papa's face softened, eyes sparkling with excitement. “We hope so.”

“But...” He looked down at the new belt that had been made for him. “Why do I need this?”

“You'll see,” his Papa told him before kissing the top of his head. He looked at Belle then. “Are we ready?” She nodded and stood, holding out her hand for Gideon to take, even as she draped an arm through Rumple's.

Together the three made their way to the front door of the place they had spent the last year calling home. As always, he and his father were forced to pause while his mother hovered, staring into the living room as if looking for the final, forgotten item to put into one of the boxes or crates.

“I'll come back for it all when we're settled,” his papa told her. He said the same thing whenever they left, but it never seemed to make her ready. She had to be ready on her own. That was what Papa always said, when his mother wasn't around to hear.

Finally, the door was closed and they faced the green space that lead to the road. Rumplestiltskin pulled a bean from his pocket and tossed it forward, causing a ring of sparks to fly out from the ground where it landed. The bright light formed a circle that spun and spat like the sparkling fire toys Gideon loved to watch at night celebrations.

He blinked in surprise. "Papa..."

"Well, that's new," his mother said at the same time.

“They warned me it might be different,” his papa shouted in an uncertain voice as he squinted at the burning edges of the circle they faced. The noise of the whirling portal was like the wind of a horrible storm. “The latest beans come from a new harvest. Some kind of hybrid.”

"Is it safe?" Belle moved closer, put her hand on his papa's shoulder and squeezed. It was supposed to look like every other touch, but Gideon could see the white in her knuckles, showing her worry.

His papa hesitated, then shrugged. “Should be fine,” he told them in a voice that Gideon wanted to believe but couldn't quite. “The giant knows, I should think." He turned and lifted the end of Gideon's new belt, gripping it tightly. "Whatever happens, son, don't take this off. Do you understand?”

Gideon nodded as the three of them stepped into another land.

* * *

The portal let them out in the middle of a cobblestone street. The sun was low and bright in the sky, a sure sign of the morning hour. They had been lucky to arrive in the earliest part of the day. Any later and the roads would have been busy with people. For now, the quiet allowed them to take in their surroundings in peace without being run over on a busy city thoroughfare.

Rumplestiltskin stepped to the curb, bringing his wife and son with him. He looked up and down the rows of buildings, memorizing their location and taking in the culture of the place. It seemed surprisingly modern for a magical realm, though the architecture did bring back memories of old cities in the Enchanted Forest. The various tweaks and accents along the road hinted at an evolved technology. There were bulbs in the street lamps and the hinges and handles on the doors all appeared sleek and contemporary. Europe, he decided finally. Perhaps somewhere in the United Kingdom...

"It's like home," Belle said with awe as she alternately gazed up at the roofs and peered in through windows. “This could be any town in the Enchanted Forest.”

“I was thinking England,” Rumple amended as he took a step forward. “But both make a good match. There was certainly a feel of home in Europe as well.” A tug in his hand reminded him that he was still tethered to Gideon.

“Papa," the boy told him."You can let go now. We made it."

Rumple turned a smile at him."I'm afraid I can't," he said tenderly, hating that he was keeping things from his son. For Gideon's safety, he and Belle had agreed to keep the nature of the local magic a mystery for as long as was possible. Neither of them wanted him lost to the realm forever. "You see, this realm has a very special kind of magic, one that might try and take you away from me. I need to hold on until I am sure you will be safe. All right?”

Confusion and concern crossed Gideon's face, but he nodded his agreement. “All right, Papa. But if more people show up, can we... at least make it look less like you have me on a leash?”

A laugh erupted from Rumple, creating a strange tingle throughout his body, but when his son scowled at him, the sensation stopped. “I'm sorry.” The apology came with a playful scrubbing of the boy's head, causing him to grunt and twist away. “There are people here who wear something similar,” Rumple explained finally. “You'll see.”

“Well, can I at least know what kind of magic I need to be ready for?”

Rumplestiltskin thought about his options. Telling Gideon what to expect might cause him to use the magic unnecessarily, putting him in a situation that the unschooled had difficulty getting out of. Not telling him would, of course prevent Gideon from purposefully using the magic, but might cause a panic if he were to stumble across it by accident. He weighed this thinking with the fact that he had made a promise to Belle and sighed heavily under the weight of it all.

Standing ahead of them, Belle unknowingly put an end to the debate. "Where do we start?" She looked back at them with such love and excitement in her eyes that Rumple began to feel the flutter of pure joy rise inside of him.

He cleared his throat to center himself and nodded down the street."That looks like an inn a few buildings down. We can get a room and then explore a bit after we have eaten.”

Belle beamed and hurried back to take his arm, kissing his cheek once she reached him.

Gideon rolled his eyes playfully as they walked on, though one hand was rubbing idly at his belly. After a few strides he made a face, wrinkling his nose and scrunching his eyes tight. "I don't think... I don't think I feel well. My stomach is... different.”

"That's the magic here,"Belle told him. "I feel it too. It's a little bit like butterflies or bubbles floating around all inside of me."

“Try not to think on it too much,” Rumple told them, trying to hold the rope tightly without giving away his worries. "Everyone in this realm has magic. They are born with it and grow up with it. They are so used to the feel of it that the price of the magic doesn't bother them. The truth of this place is not that everyone here has magic, but that the magic here has everyone."

"It sounds dangerous," Gideon said with a swallow.

"Only if I let go." Rumple insisted as they reached the inn.

At this,Gideon took his hand and squeezed hard. Rumple squeezed back in reassurance as they went inside.

* * *

The lobby that greeted them was tiled in dark stone and had rich, wooden accents in the cream colored walls. While the decor certainly implied that the inn was older, the structure itself had been modernized. Electric bulbs hung from the ceiling, shining their warm glow on a room that had a “restored” quality about it. The historic stone exterior had easily hidden the updated beauty of the building's interior, Belle thought, as they were approached by a woman with a friendly greeting and a bright grin.

“Welcome,” she said with a bubbly cheer that was almost infectious. “Can I help--?”

The moment Rumple turned to greet her, the woman froze, her eyes narrowing to slits. “We haven't had your kind here before,” she said sternly. “It isn't that you aren't welcome, you understand, but I couldn't claim to know your needs or be able to fill them.”

Belle saw her husband's chest expand slowly and then contract as he let out a long, slow breath, and caught Gideon doing much the same. Though Rumple's smile never wavered, the boy's turned to a frown. She knew the slight hurt both the father and the son who took such pride in the man he called Papa. Eight years of traveling to places that never heard of the Dark Curse made these kinds of introductions a part of their distant past and now here they were, suddenly reliving everything in one conversation.

“I understand that this is a realm of light magic,” Rumple answered warmly. “And I did expect to stand out like a red rose on a bush of white flowers, but I can promise you I have no use for the magic I was cursed with. My wife, my son, and I are on a quest of sorts, to rid me of the darkness so that I can continue sharing a life with them as it was meant to be lived.” He sighed and adjusted his stance, gesturing out into the lobby and back to the street. “We had hoped that coming here, we might find a way to at least lighten the burden, even if we couldn't find a cure.”

“My husband has not cast even the simplest spell in over nine years,” Belle insisted as she pressed closer to his side. “He gave up magic when our son was born.” It was a simplification of their history, but they never explained Gideon's full history to anyone, even in a realm that would understand it.

The woman stared at them for an exceptionally long time, her eyes locking with Rumplestiltskin's and peering as if they could drill a hole through them straight to the truth of the matter. When she finally nodded, it was a short, sharp gesture of acceptance. “I believe you,” she said at last. “You do realize you will be met with much the same greeting wherever you travel in this realm?”

Rumple nodded slowly. “I knew what I faced before we left home,” he admitted. “I am willing to wear cuffs that prevent the casting of-”

“Oh, no, no,” the woman snorted, flapping at the air as if warding off complete nonsense. “That certainly won't be necessary. I simply mean to warn you that your welcome will not always come so easily with other members of the community.”

The corners of his mouth twitched up in a weak smile. “I expected that, yes.”

“Well...” She looked at each of them in turn, sizing them up again as her bubbling personality returned. “We only have one room available, but you are welcome to it. It has one bed, and we can bring a cot for the boy.” She talked as she strode across the room to a desk at the corner, then pulled open a drawer and took a key. “My name is Jane and if your travels brought you here, then your visit was most certainly meant to be.”

“Why is that?” The question was Gideon's.

“Because the magic here takes you to where you are most needed. Everyone in this realm is born with this gift and it causes us to flow in and out of peoples' lives like leaves drifting on the wind,” Jane told him, bending forward over the counter to tap the tip of his nose. “One minute you're having tea with your friends, then the next... Woosh! You're off to another realm where you are needed.”

Gideon's eyes blinked. “Without a portal?”

“No portal necessary,” Jane told him. She opened her mouth to say more, but Rumplestiltskin made certain to interrupt her.

“We'll take the room, if you don't mind. It has been a long day and we would prefer to rest before our meal.” He held out his hand expectantly.

“Of course, of course.” The woman plopped the key into his palm with a winning smile. “If you need anything, simply ask.”

“We will,” Belle said as they made their way upstairs.

The room was on the second floor and Rumple handed Gideon the key so that he could do the honors. Eagerly, the boy unlocked the door and opened it a crack to peek inside, then burst into a fit of laughter.

Worried that the magic might claim him in his lighthearted state, Belle put on her best worried expression and added a sterner tone than was necessary to keep him in line. “Gideon! We are out in the hallway.” She shushed him and nudged him to go inside.

“Sorry,” he said as he entered. “I couldn't help it. Miss Jane said the magic would take us where we needed to go and she was right. Papa needed to go here.”

“Why say that?” Rumple's eyes narrowed as he stepped forward, then blinked in surprise at the room they had been given.

Belle grinned at him. “Oh, look, Rumple,” she said, placing a hand on his chest and throwing out her best mocking tones as she tried not to giggle. “It's purple.”

The walls were actually a pink that practically matched his old home, but the four post bed was covered in a rich purple bedding with golden accents, a pattern that was perfectly duplicated in the rest of the room's furniture.

“Very funny,” he grumped as he shut the door behind them.

* * *

In here will go one of their adventures, in which Belle and Gideon meet a shopkeeper who does actually need their help, and who might be able to help them in return. But let's skip that for now so that we can get to the prompt that started this whole work in the first place.

* * *

Rumplestiltskin strolled quickly down the cobblestone street, the heels of his shoes clicking out his nervousness. Belle had insisted that she and Gideon wouldn't go far on their little excursion, yet up to this point he had been inside of every shop within three blocks of the inn and he was continuing to miss them. Each shopkeeper, without exception, had first given him one of the calculating glares that he had become used to in this realm, then pointed him farther down the street, across to the next block, or indicated that the pair had just turned the corner.

There would have to be rules, he decided. The next time they traveled to a realm without cell phones, the three would stick together no matter what.

The sound of shattering glass caught his attention and Rumple spun on his heel to locate the origin of the noise. Across the street from where he stood, he saw an open shop door and from the door came a collection of painfully recognizable giggles.

“Oh no,” he muttered to himself as he sped to the entrance. “No, no, no...”

A week. They had managed to keep the magic from getting to Gideon for a whole week and now, after all of that effort, it seemed as if they had failed.

Dashing in to the shop, Rumplestiltskin took in his surroundings. The items for sale all seemed in perfect condition except for a single vase that had toppled to the stone floor. He stood beside it and rotated in place, checking each corner and shadow of the room. The silence was wrong, not just because he was certain he had heard laughter, but because the hush in the room felt forced.

Without warning, an explosion of laughter erupted from above, the kind of outburst that could only mean someone had been holding their breath in order to contain themselves. Slowly, Rumple tipped his head upward, lifting his gaze to the ceiling, where Belle, Gideon, and a woman who was presumably the shopkeeper, were drifting in the rafters.

He circled below them, staring up in amused disbelief and felt a grin widen on his face as he positioned himself under Belle's skirt. The hotel manager had quietly warned her of the dangers of such garments in this realm, but Belle hadn't listened and now she would be paying the price, though Rumple suspected Belle wouldn't mind paying it to him.

“Not that I'm complaining about the view,” he finally called up to them, a statement which made Belle squeak and fiddle with the fabric tangling around her legs. “But... How on earth did you get up there?”

“We laughed up!” Gideon chortled as he made swimming motions with his arms. “That's what the magic here does, Papa. It's why we felt bubbly all the time. The magic isn't just light magic, it makes you float when you feel light.”

“Yes,” Rumple harrumphed as he shifted position so that he was under Belle again. “Something I warned your mother about repeatedly.” He gave her a wink and a wicked grin.

“Rumple!” Belle shouted at him and kicked a foot in the air as if to shoo him away, but only succeeded in tipping herself to an angle that gifted him an even better view.

The woman beside her helped to set Belle straight, then waved down at the ground below. “Hello,” she said with a winning smile. “I'm Nina Twigley.”

Despite himself, Rumple found his hand raising in the air and returning the wave. “Hello,” he said cordially. “Can I presume you are the one responsible for my family's predicament?”

“Oh yes,” Nina admitted with a giggle. “It's quite my fault. I don't really know what got over me. You see, I'm one of the few in this realm who has trouble with this sort of thing and-”

“It's my fault, Papa,” Gideon told him. The boy was now doing somersaults in the air. “We were talking about Miss Twigley's string being like mine and that she used it to keep herself still so she could work, and then I made a joke. Well, I didn't mean to, but I did. Then she started laughing and floating and when I tried to pull her down, I slipped and then I started laughing and then mother did because I was floating upside down...”

“It's no one's fault,” Belle insisted. “We were just having a good time.”

“Well now that you've had one, I would like my family back, please,” Rumple told her. “I was expecting them for dinner.”

Nina waved her arm as if she were directing traffic. “Come and join us, then,” she told him, in no uncertain terms.

“I can't,” Rumple answered simply.

“Oh.” Nina's face relaxed, her smile disappearing as she lost several inches of lift. “Yes, of course, I'm so sorry, I didn't mean...”

Rumple shook his head, feeling the weight of his darkness more than ever before. He wished he could experience what his wife and son were going through right now. Well, perhaps not the flying part. He hadn't ever wanted that, not even when he was in Neverland, but the drifty feeling of pure light would be nice to feel just once. He also had to admit that there was some appeal to the idea of catching Belle as she drifted by and hiking up her skirts to test his abilities while adrift.

“I'm afraid we have to go,” he said finally.

“Do we have to?” Gideon began to sink to the floor. The motion was at first slow enough that he didn't notice, but once he was halfway, he blinked in surprise. “What's happening?”

“Your heart isn't light any more,” Nina told him. “When you have to be serious or sad or mad... Your heart gets heavy and the magic stops working.”

Rumple caught Gideon's ankle once it was within reach and pulled him down to his side, then took hold of the long belt they had been using and grasped tightly to the end. “All right?”

Gideon nodded. “Yes, Papa. But do we have to go?”

“You do if you want dinner, and I thought you were a growing boy.” The tease sent Gideon to chuckling and drifting again. Rumple smiled and nudged him back to the ground, glad that he still had the power to make his son happy

Once Gideon was settled at his side, Rumple looked up at Belle and held a hand to the sky for her. “Sweetheart,” he whispered, unable to speak words that would possibly hurt her.

“I can't,” Belle told him.

Her words provided the means for the perfect sadness between them and Rumple spoke it tenderly. “Then you will be without us forever.”

Belle dropped like a stone and Rumple rushed to catch her, slipping an arm around her waist and guiding her to the floor with the kind of precision that only years of dancing together could produce. Once she was in his arms, he kissed her, pressing his body against hers.

“I'm sorry, my love,” he whispered. “I had to-”

“I know,” Belle said as she draped her arms over his shoulders and clasped her hands at his neck.

Behind him, Rumple heard the thud that could only signal Nina Twigley's return to the shop's floor. He turned to the woman once she was settled and gave a slight bow. “I'm afraid we must say goodnight, Miss Twigley. I think my son is in need of flying lessons.”

With another giggle, Gideon began to drift, but Rumple kept his hand firmly on the boy's belt. After speaking her own farewell, Belle's fingers wrapped over his and the two of them walked their son back to the inn as if he were a laughing balloon.

#a monthly rumbelling #amr #rumbelle #travel #missing years #family #new realm #a monthly rumbelling january 2020

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hadooptpoint · 8 years ago

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greylagwriting · 6 years ago

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A Brief Guide to The Mage and the Minotaur

@grittygambit TMATM is a high-fantasy, lighthearted story about a human mage's get-rich-quick scheme of marrying a minotaur prince for his (hopefully large) dowry. It's the most fleshed out IP I have, in both plot and world, and of all the ideas I have, this is the one I'd most want to be published.

---

The magic system here is as follows: in the air is an invisible, almost intangible force called astrata, which is magic in its purest form. It is thicker in some areas of the world, but can be found everywhere. With practice and training, anyone can learn to channel astrata through their bodies or a conduit (such as a wand or staff) and cause it to take different forms. Mages are not rare, and anyone can be one, but the knowledge of magic is something not readily known to most people.

Astrata is the source of life itself, imbuing every living being from the moment they're born to the second they die. As such, magic takes three main forms: animation, fusion, and fire. It is most often used for healing.

Mages can imbue inanimate objects with magic to make them become animate and move under their own power. There are some who animate the bones and bodies of the dead, but such necromancy is very controversial.

Another facet of magic is that it can merge two living beings together. Minotaurs came about from the natural fusion of humans and cattle, while griffins came from fusion mages who magically combined housecats and hawks.

Fire magic is the most dangerous. Since astrata is pure energy, it an become quite volatile when compressed and concentrated. Channeling too much magic at once through anything can result in skin damage, burns, or even spontaneous combustion. With long years of patience, training, and careful study, mages can learn to control fire magic, but even the best can make mistakes and spark massive conflagrations.

---

There are three major races in the world — humans, goblins, and minotaurs.

Goblins are by far the most prominent race next to humans. They resemble tall, lanky humanoid hyenas, much like D&D’s gnolls. Like bees, goblins have a eusocial lifestyle, with each goblin colony headed by a queen and her many, many children. Female goblins serve as the colony’s workers, soldiers, etc., while male goblins, known as drones, leave the colony upon maturing to mate with the queens of other colonies. It’s strictly forbidden for drones to mate with queens of their own colony; some colonies take extreme measures and prevent drones from even speaking to females.

Most goblins have beige fur with dark brown spots, but on rare occasions, a female goblin with red fur is born. This goblin is known as a princess, and upon maturing, will leave the colony with a retinue of soldiers and a few drones from neighboring colonies to form her own and become queen. Any female goblin can become a queen, however; red-furred ones are selected to become queens mainly because of tradition.

Goblins are known to build massive forts around their colonies, often building underground, high in a mountain, or in other places that aren’t easily accessible. They are secretive, and, save for the drones, rarely leave their colonies. It’s rare for them to mingle with the races of the outside world.

Minotaurs resemble humanoid cows, and there are several different species that mirror real-world cows - longhorn, angus, highland, and so on. Minotaurs live in loosely-connected clans, with each of the clan leaders being allied with each other. There is no one leader for all the clans, however, and they are mostly independent. Minotaurs prize the arts, math, science, and philosophy, and share their findings with the outside world.

Other races are present, most being natural, magical fusions of humans and various animals, though they aren’t as prominent.

The main characters are as follows.

---

Ev: A young mage from the mountain village of Penvida, Ev made a living as a yarn spinner. They is quite talented at fire magic, and has developed a branch of it that they call light magic. As a light mage, Ev can create blinding flashes and beams of light in various colors using a myriad of crystals. However, Ev soon discovered light magic had a side effect of severe hair loss, and they ended up bald after performing too much of it.

When Ev was 20, Penvida was destroyed by Yo-Sho (see below). Ev and Xathandua were among the only survivors, but Ev did seek revenge. Instead, they seeked a way to rebuild the village and restore it and its unique architecture to its former glory. Ev has made it their life's mission to do this, and will stop and nothing to achieve the goal.

Ev is very much a "do no harm, but take no snack" sort of person. A sworn pacifist, Ev refuses to kill unless it is unavoidable, but isn't above blinding someone in self-defense.

Prince Enduring: The youngest of three siblings, Endur is the child of a minotaur clan leader. Unlike his siblings, Endur is not conventionally attractive among minotaurs due to his smaller-than-average horns. When he was young, Endur lived to pull pranks on others and just make trouble, and still has not grown out of his ways. As a result, his mother, Queen Plans-Ahead was desperately trying to get Endur out of the clan. Her ultimatum was simple: shape up, or be banished from the clan forever.

Eventually, Endur realized the predicament he was in. Unwilling to strike out all on his own, he came up with a plan: marry someone who could take care of him and move away from the old clan, which is how he came to marry Ev. After discovering that Ev married him for money, Endur became somewhat ashamed, and decided to make it up by retrieving a magical war axe once belonging to his ancestor. Endur’s idea was that, upon presenting the minotaur clan with the axe, they would receive money for Ev and respect for Endur.

Xanthandua: The son of the local death priest, Xathandua grew up in Penvida among a lot of bones and vultures. From an early age, Xath was fascinated with animation magic, and even experimented with resurrection in secret, which is forbidden in Penvida. When Penvida was destroyed, Xath vowed to get revenge on whoever did it.

Thinking himself too weak to go on this quest for justice, Xath seeked out the strongest mage around to train under, and ended up apprenticed to Yo-Sho, the very mage who caused the destruction.

Neither Xathandua nor Yo-Sho are aware of the situation, and he is eager to serve as Yo-Sho's right hand man.

Yo-Sho: Yo-Sho is a pascanii, a creature resembling a humanoid snapping turtle. She hails from another continent where the study of magic is very restricted. She’s one of the few mages with complete control over fire magic, and has a lust for power. In her travels, Yo-Sho discovered Penvida, the village Ev and Xathandua come from. Yo-Sho used the village as a testing ground for spells, raining down fire and burning light. The village soon burned to the ground, leaving Xathandua and Ev among the only survivors. Yo-Sho’s goal is to strike fear in others with her magic, and rule with a burning iron fist.

Tillia: Tillia is a young, red-furred goblin who was chosen to become queen. Accompanied by soldiers and drones, Tillia set out to form her own colony, but was met with disaster and only she survived. Tillia soon decided she would give up on becoming a queen, instead mingling with the rest of outside society. She has an adventurous spirit, and makes a living guiding adventurers through treacherous terrain. Tillia acted as a guide to the party when it came time to retrieve the axe from her old colony.

#WIP: TMATM

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rossana-fashion-blog · 4 years ago

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Evaluation

In this project I was trying to achieve different ways to show the different types of architecture from Old vs. New. I did this by, showing different primary evidence highlighting buildings with Victorian and moderns structures. The experimentation with different techniques allowed me to produce different samples to show different final samples also, samples from previous sessions were used to help me through the design journey of my sketchbook.

I used my primary images to develop my research by creating collages with them as well as, use all the different techniques I experimented in this module.My primary evidence links to my project because it shows my narrative, where I wanted to show how architecture has developed through time. I practically used all my primary research to create samples using different techniques I learnt through this module.

In this module I was able to experiment with different techniques such as, Print: generic blank screens & generic screens exposed with geometric shapes,procion,disperse dye and digital printing. I found these specific techniques a bit challenging at first, however I really enjoyed disperse dye which was was one of my strengths, which I developed further to make more of it for my final samples. Another technique I was able to experiment was Embroidery : pin tucks, pleats,couching, appliqué with free hand embroidery & aqua film. I found these techniques somewhat challenging but I did enjoy using appliqué with free hand embroidery and aqua film which I was able to produce good samples with it.However, I found pin tucks,pleats, couching to be very challenging and this was one of my weaknesses. Another technique was Weaving: plain weaving and weave structures.I found plain weaving to be one of my strengths because I was able to use images along with different yarns which were successful.Lastly, Sketchbook techniques such as, mark making,layout techniques and collages. I found that collaging was really important for my narrative which was one of my strengths to show my primary research throughout my research journey.

Majority of the the techniques listed above were successful however some weren’t such as, procion, some disperse dye samples,appliqué with free hand embroidery and some mark making techniques. These techniques were somewhat challenge at first, and some didn’t come out great for, example the disperse dye design I made in print session 2 faded so when I used it again the dye was fairer which made hard to obtain a clear print from it. If I was to refine these experiments again, I would use drawing more accurately before using appliqué with free hand embroidery for more guidance.

A huge part to my planning and production was using primary photos which I drew inspiration from secondary research such as artists. However, a lot of my research was mostly sparked by different ways I found to collage as I went a long. Furthermore, I planned what I would do in my final samples workshops to help me use my strength techniques which allowed me to create different type of samples. Some samples when producing did not come out as expected and one of my problem solving techniques to solve this was to use it as backgrounds or dismantle it and use it around my primary photos.

My final outcome was mainly different samples using all my strongest techniques or the ones I enjoyed the most to create different type of samples, using my primary pictures while using secondary research for inspiration. I am pleased with a lot of my final outcome samples because I was able to do them better than the first time I tried them.

Reference List

1. Anastasia Savinova “Genius Loci Series, Paris,2013”

2. Anastasia Savinova “Genius Loci Series, Noorland, 2015”

3. Henri Matisse “The Snail 1953”

4. Henry Moore “The Artist's Hand II 1979”

5. Matt Peers “ The Protagonists Of A Private Play Gallery”

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karonbill · 4 years ago

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HCIA-Big Data V3.0 H13-711_V3.0 Real Questions and Answers

Anyone who want to achieve the HCIA-Big Data Certification can choose PassQuestion HCIA-Big Data V3.0 H13-711_V3.0 Real Questions and Answers for your best preparation.All of our H13-711_V3.0 Questions and Answers are created by our experts that will help you achieve the best outcome in a short time. It will help you build confidence and you will be able to find out important tips to attempt your H13-711_V3.0 exam.Make sure to go through all the HCIA-Big Data V3.0 H13-711_V3.0 Real Questions and Answers that will help you prepare for the real exam and you will be able to clear your HCIA-Big Data V3.0 exam on the first attempt.

HCIA-Big Data Certification

After passing HCIA-Big Data Certification,you should learn the knowledge of Technical principles and architecture of common and important big data components. Knowledge and skills required for big data pre-sales, big data project management, and big data development.This exam is suitable for those who desire to become big data engineers. Those who desire to obtain the HCIA-Big Data certification. Junior big data engineers.

Notice: There are currently two versions you can take for your HCIA-Big Data Certification, HCIA-Big Data V2.0 certification will be brought offline on February 28, 2022.HCIA-Big Data V3.0 is now recommended.

Huawei HCIA-Big Data V3.0 Certification Exam Information

Certification: HCIA-Big Data Exam Code: H13-711 Exam Name: HCIA-Big Data V3.0 Language: ENU Exam Format: Single Answer, Multiple Answer, True-false Question Exam Cost: 300USD Exam Duration: 90 mins Pass Score/ Total Score: 600/1000

Exam Content

HCIA-Big Data V3.0 exam covers: (1) Development trend of the big data industry, big data features, and Huawei Kunpeng big data. (2) Basic technical principles of common and important big data components (including HDFS, ZooKeeper, Hive, HBase, MapReduce, YARN, Spark, Flink, Flume, Loader, Kafka, LDAP and Kerberos, Elasticsearch and Redis). (3) Huawei big data solutions, functions and features, and success stories in the big data industry.

Key Points Percentage

1. Big Data Development Trend and Kunpeng Big Data Solution 3% 2. HDFS and ZooKeeper 12% 3. Hive - Distributed Data Warehouse 10% 4. HBase Technical Principles 11% 5. MapReduce and YARN Technical Principles 9% 6. Spark In-Memory Distributed Computing 7% 7. Flink, Stream and Batch Processing in a Single Engine 8% 8. Flume - Massive Log Aggregation 7% 9. Loader Data Conversion 5% 10. Kafka - Distributed Publish-Subscribe Messaging System 9% 11. LDAP and Kerberos 5% 12. Elasticsearch - Distributed Search Engine 5% 13. Redis In-Memory Database 5% 14. Huawei Big Data Solution 4%

View Online HCIA-Big Data V3.0 H13-711_V3.0 Free Questions

In Fusioninsight HD, which of the following is not part of the flow control feature of Hive? (Multiple choice) A. Support threshold control of the total number of established connections B. Support threshold control of the number of connections that each user has established C. Support threshold control of the number of connections established by a specific user D. Support threshold control of the number of connections established per unit time Answer: ABD

Which of the following descriptions are correct about Fusionlnsight HD cluster upgrade? (Multiple choice) A. It is not possible to manually switch between active and standby OMS during the upgrade process B. Keep the root account passwords of all hosts in the cluster consistent C. Keep the network open. Avoid abnormal upgrades due to network problems D. Expansion cannot be done during the observation period Answer: ABCD

When the Fusionlnsight HD product deploys Kerberos and LDAP services, which of the following descriptions is correct? (Multiple choice) A. Before deploying Kerberos service, LDAP service must be deployed B. LDAP service and Kerberos service must be deployed on the same node C. Kerberos service and LDAP service are deployed on the same node to facilitate data access and improve performance D. LDAP service can be shared by multiple clusters Answer: AC

Which of the following targets can Fusioninsight HD Loader export HDFS data to? (Multiple choice) A. SFTP server B. FTP server C. Oracle database D. DB2 database Answer: ABCD

What are the key features of Streaming in Huawei's big data product Fusioninsight HD? (Multiple choice) A. Flexibility B. Scalability C. Disaster tolerance D. Message reliability Answer: ABCD

Which of the following sub-products does the Fusioninsight family include? (Multiple choice) A. Fusioninsight Miner B. Fusioninsight Farmer C. Fusioninsight HD D. GaussDB 200 Answer: ABCD

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designresearchsammy · 4 years ago

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Draft Critical Commentary

PARAGRAPH 1

CONTEXT 1

Increase interest in tactile materials as the world becomes more digital

surface/craft. Texture working with colour to create meaning

This context has been important for my own design ideas, encouraged me to explore new making techniques outside of digital format, while also incorporating this into digital work

sparked an interest in surface design, different ways of documenting surface

the importance of learning through making and the relationship between the maker, the materials, the process of making and the work

Newell,L.(2007). Out of the Ordinary. V&A Publications.

“We are invited to concern ourselves with the process of making and this, in forn, leads to reflections on the nature of work, time consumption, the physical rhythms of making, replications and trompe l'oeil, technology and virtuosity. The way in which ordinary materials can be made unfamiliar and precious brings to mind a long history of stories and anecdotes that narrate something of the strangeness of making, its hidden secrets and its capacity for enchantment. Let's begin with virtuosity, a term often linked to a more practical concept, that of technique. The relationship between technique and making is mysterious, prompting thoughts on the education of artists. In schools of art and design, do we require separate departments of painting, sculpture, metalwork, textiles, ceramics and glass, each teaching different techniques? Or should these skills be 'needs-led', to be mastered 'as and when’?”

———

Openshaw,J, (2015). Postdigital artisans : craftsmanship with a new aesthetic in fashion, art, design and architecture. Frame Publishers.

Digital technology now mediates much of our interaction with the world, and a vast majority of the images that we absorb daily come through a screen. The digital comes with its own aesthetic framework that cannot help but colour our experience of the world, and change our expectations of the objects that surround us. As the digital becomes ever more pervasive however, there is also a return to physical experiences that technology cannot satisfy. This is true across sectors, from immersive theatre to vinyl records, and although digital will undoubtedly dominate our future, there are pockets of resistance. This book will look at contemporary artisans who are deeply influenced by the digital world in which we live, but who reject processes such as 3D printing as a final output. Inspired by the internet and a screen-based aesthetic, they choose to craft things by hand, rendering a postdigital mindset in tactile materials, such as metal, glass and wood. It represents a return to the physical in the digital age.

(just the abstract, need physical book from library but I think this text will be helpful)

PARAGRAPH 2

METHOD 1

several methods relating to the context of surface and tactility

First tactile method of making which I was inspired by and developed my own skills in was needle punch method. This method of making requires a needle punch, yarn and monks cloth. The needle punch tool allows you to push yarn through the fabric which creates a small loop when it is pulled out. These loops are what forms the rug or wall covering.

I am particularly inspired by New Zealand artists Olivia Edginton and Leah Creaven. Edginton’s making style combines colourful, overlapping, geometric shapes contained in a checkerboard format. Creaven tends to use a more neutral, earthy colour palate with organic shapes. Both artists experiment with different textile mediums and techniques to create art that has a unique tactile quality while also being visually appealing.

Earlier this year I created a wall covering using the needle punch method, I was interested in exploring the life cycle of nature, particularly focusing on the beauty of natural decay and the opportunity this provides for new life. I used mostly organic and abstract shapes and experimented with a range of textile mediums. Some sections of the yarn were left much longer so that they were hanging off the piece, mimicking overgrown weeds. Holes were cut into the material to create the look that it was rotting/breaking down. Natural, earthy colour palette was also used to make the piece look as realistic as possible. The result was a physical, tactile object that could be perceived visually and through touch.

Other methods which are important to my work and within the context of surface and craft..

Printmaking techniques, screen print, cyanotype, gelatine plate

PARAGRAPH 3

CONTEXT 2

Make notes outlining ideas for your second contextual discussion here:

The role of illustration in commentary, storytelling, and identity

"Illustration practice is not judged purely by visual literacy and technical qualities, but also requires intellectual engagement with its subject matter”

Alan,M. (2017). Illustration: A theoretical and contextual perspective. AVA Academia.

PARAGRAPH 4

METHOD 2

Illustration style

looking at my artist models that I am influenced by, also linking back to texture in a digital sense, overlapping, grain, abstract, detailed, bright colours

‘Wastopia’ by Qianhui Yu, short animated film, explores the issues surrounding attitudes to waste disposal and the environment pollution that follows as a result of these attitudes

playful, visual style is juxtaposed with much darker and serious themes as mentioned earlier such as pollution and addiction to social media - linking back to illustration role in commentary and storytelling

enjoy the illustration style that Qianhui Yu uses which is colourful, surreal, and uses highly detailed texture - illustration is an area I am working on developing my skills in and I am particularly inspired by her style

Also talk about Xi Zhang, illustrations blend both abstract and realism techniques to create a dreamy visual experience for the viewer, her work is mostly quite self reflective, story-telling feel again linking back to illustration role in storytelling and identity

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madhumadhum · 2 years ago

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Online Big Data Hadoop Certification at H2K Infosys

H2K Infosys offers a comprehensive Big Data Hadoop certification course that covers all the essential topics you need to know to become a Hadoop expert. The course is taught by experienced instructors who have a deep understanding of Hadoop and its applications.

The course begins with an introduction to Big Data and Hadoop. You will learn about the different types of Big Data, the challenges of managing Big Data, and how Hadoop can be used to solve these challenges.

The course then covers the core components of Hadoop, including HDFS, MapReduce, and YARN. You will learn how to use these components to store, process, and analyze Big Data.

The course also covers the latest developments in Hadoop, such as Apache Spark and Hive. You will learn how to use these technologies to build scalable and efficient Big Data applications.

In addition to theoretical knowledge, the course also provides you with hands-on experience with Hadoop. You will work on a variety of projects that will give you the skills you need to be successful in a Hadoop job.

Upon completion of the course, you will be eligible to take the Hadoop Certified Developer Associate (CHDA) exam. This exam is a globally recognized certification that validates your skills in Hadoop.

Benefits of Big Data Hadoop Certification at H2K Infosys

There are many benefits to getting a Big Data Hadoop certification from H2K Infosys. Here are a few of the most important benefits:

Who Should Get a Big Data Hadoop Certification?

The Big Data Hadoop certification course is designed for anyone who wants to learn about Hadoop and its applications. The course is ideal for:

How to Get Started

To get started with the Big Data Hadoop certification course, you can visit the H2K Infosys website. The website has more information about the course, including the syllabus, pricing, and enrollment process.

You can also contact H2K Infosys customer support for more information.

Conclusion

If you are interested in a career in Big Data, then a Hadoop certification is a great way to get started. The Big Data Hadoop certification course from H2K Infosys will teach you the skills you need to be successful in a Big Data job.

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outsourcebigdata · 4 years ago

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Sandboxes and their advantages

If we talk about the development of Hadoop technology then there are two companies which are doing a lot in this field. One is Hortonworks and another is Cloudera. These companies are developing a lot of new ideas and software in the field of Hadoop to make it easier to use and developing a lots of applications on them. These companies provide tools to use and learn Hadoop.

Hortonworks provides “Hortonworks Sandbox” and Cloudera Provides “ Cloudera Quick start VM ” . These tools are a package in which Hadoop is configured along with the tools is needed in developing Hadoop environment. We will discuss about the benefits of using these tools.

Hortonworks Sandbox

This sandbox having the Hortonworks Data platform in an easy form but it comes with a terminal which is easy to handle. This sandbox provides

A virtual machine with Hadoop configuration.

Some basics about Hadoop to get you started.

Different tools that will help you in the Hadoop ecosystem like Apache Hive, Apache Pig, Apache HBASE and many more.

The Hortonworks Hadoop Sandbox is delivered as a virtual appliance that is a bundled set of operating system, configuration settings and the applications that work together as a unit. The virtual appliances runs in a virtual machine with the application to the host operating system. To run Hortonworks sandbox you must install one of the supported VM environment on the host machine either Oracle Virtual Box or VMware Fusion (Mac) or Player (Windows/Linux).It doesn’t have any user interface like “Cloudera sandbox”. It having an interface like prompt command in which you need to write command line to execute any operation.

Cloudera Quickstart VM

Cloudera also provides the tools for learn and use Hadoop. From Hortonworks it is “Hortonworks Sandbox” and from Cloudera it is “ Cloudera Quickstart VM” . It is also a virtual machine along with the package of different tools and software which is used in Hadoop related work. It is available in free but along with Cloudera manager it’s available for 60 days trail and paid version. It includes different software like Hadoop, HBASE, Spark, Oozie etc. Cloudera Quickstart virtual machine provides some basics to get you started. It is frequently used in multi node clusters.

Comparison between Hortonworks Sandbox and Cloudera Quickstart VM are:

Hortonworks is open source i.e. completely free whereas Cloudera Quick VM is also completely free but with Cloudera manager it having a free 6o days trail and paid version

Both support Map Reduce as well as Yarn.

Both distributions have master-slave architecture.

Horton works having “ Ambari ” interface while Cloudera having “ Hue” as GUI.

Both are Linux supported.

Benefits of using these sandboxes in OSP to offer unique setup to clients are:

Both are open source so on the cost aspects it will be a big benefit. We will have Hadoop configuration with different supporting software like Hive, HBASE, Eclipse, Spark and many more. So we can provide better service to client without worrying about the setup cost.

As we discussed above that sandboxes contains all the supporting tools used in Hadoop ecosystem so it will be beneficial to work in Hadoop environment because of availability of all tools as a package. It will increase the productivity.

Sandboxes platforms are easy to use form. We can add our own data sets and connect it to existing tools and applications.

These sandboxes also provides some basic of Hadoop and other tools to learn. It will helpful to a new employee for a new setup.

#Data Management

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craigbrownphd-blog-blog · 5 years ago

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If you did not already know

MatrixDS Work on your own projects, collaborate with others, and share with the whole community on a secure cloud-based platform. … MediChainTM The set of distributed ledger architectures known as blockchain is best known for cryptocurrency applications such as Bitcoin and Ethereum. These permissionless block chains are showing the potential to be disruptive to the financial services industry. Their broader adoption is likely to be limited by the maximum block size, the cost of the Proof of Work consensus mechanism, and the increasing size of any given chain overwhelming most of the participating nodes. These factors have led to many cryptocurrency blockchains to become centralized in the nodes with enough computing power and storage to be a dominant miner and validator. Permissioned chains operate in trusted environments and can, therefore, avoid the computationally expensive consensus mechanisms. Permissioned chains are still susceptible to asset storage demands and non-standard user interfaces that will impede their adoption. This paper describes an approach to addressing these limitations: permissioned blockchain that uses off-chain storage of the data assets and this is accessed through a standard browser and mobile app. The implementation in the Hyperledger framework is described as is an example use of patient-centered health data management. … Data Fusion Data fusion is the process of integration of multiple data and knowledge representing the same real-world object into a consistent, accurate, and useful representation. Data fusion processes are often categorized as low, intermediate or high, depending on the processing stage at which fusion takes place. Low level data fusion combines several sources of raw data to produce new raw data. The expectation is that fused data is more informative and synthetic than the original inputs. For example, sensor fusion is also known as (multi-sensor) data fusion and is a subset of information fusion. … PingAn Geo-distributed data analysis in a cloud-edge system is emerging as a daily demand. Out of saving time in wide area data transfer, some tasks are dispersed to the edge clusters satisfied data locality. However, execution in the edge clusters is less well, due to limited resource, overload interference and cluster-level unreachable troubles, which obstructs the guarantee on the speed and completion of jobs. Synthesizing the impact of cluster heterogeneity and costly inter-cluster data fetch, we expect to make effective copies across clusters for tasks to provide both success and efficiency of the arriving jobs. To this end, we design PingAn, an online insurance algorithm making redundance across-cluster copies for tasks, promising $(1+\varepsilon)-speed \, o(\frac{1}{\varepsilon^2+\varepsilon})-competitive$ in sum of the job flowtimes. PingAn shares resource among a part of jobs with an adjustable $\varepsilon$ fraction to fit the system load condition and insures for tasks following efficiency-first reliability-aware principle to optimize the effect of copies on jobs’ performance. Trace-driven simulations demonstrate that PingAn can reduce the average job flowtimes by at least $14\%$ more than the state-of-the-art speculation mechanisms. We also build PingAn in Spark on Yarn System to verify its practicality and generality. Experiments show that PingAn can reduce the average job completion time by up to $40\%$ comparing to the default Spark execution. … https://bit.ly/347MumK

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siva3155 · 6 years ago

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300+ TOP PYSPARK Interview Questions and Answers

PYSPARK Interview Questions for freshers experienced :-

1. What is Pyspark? Pyspark is a bunch figuring structure which keeps running on a group of item equipment and performs information unification i.e., perusing and composing of wide assortment of information from different sources. In Spark, an undertaking is an activity that can be a guide task or a lessen task. Flash Context handles the execution of the activity and furthermore gives API’s in various dialects i.e., Scala, Java and Python to create applications and quicker execution when contrasted with MapReduce. 2. How is Spark not quite the same as MapReduce? Is Spark quicker than MapReduce? Truly, Spark is quicker than MapReduce. There are not many significant reasons why Spark is quicker than MapReduce and some of them are beneath: There is no tight coupling in Spark i.e., there is no compulsory principle that decrease must come after guide. Spark endeavors to keep the information “in-memory” however much as could be expected. In MapReduce, the halfway information will be put away in HDFS and subsequently sets aside longer effort to get the information from a source yet this isn’t the situation with Spark. 3. Clarify the Apache Spark Architecture. How to Run Spark applications? Apache Spark application contains two projects in particular a Driver program and Workers program. A group supervisor will be there in the middle of to communicate with these two bunch hubs. Sparkle Context will stay in contact with the laborer hubs with the assistance of Cluster Manager. Spark Context resembles an ace and Spark laborers resemble slaves. Workers contain the agents to run the activity. In the event that any conditions or contentions must be passed, at that point Spark Context will deal with that. RDD’s will dwell on the Spark Executors. You can likewise run Spark applications locally utilizing a string, and on the off chance that you need to exploit appropriated conditions you can take the assistance of S3, HDFS or some other stockpiling framework. 4. What is RDD? RDD represents Resilient Distributed Datasets (RDDs). In the event that you have enormous measure of information, and isn’t really put away in a solitary framework, every one of the information can be dispersed over every one of the hubs and one subset of information is called as a parcel which will be prepared by a specific assignment. RDD’s are exceptionally near information parts in MapReduce. 5. What is the job of blend () and repartition () in Map Reduce? Both mix and repartition are utilized to change the quantity of segments in a RDD however Coalesce keeps away from full mix. On the off chance that you go from 1000 parcels to 100 segments, there won’t be a mix, rather every one of the 100 new segments will guarantee 10 of the present allotments and this does not require a mix. Repartition plays out a blend with mix. Repartition will result in the predefined number of parcels with the information dispersed utilizing a hash professional. 6. How would you determine the quantity of parcels while making a RDD? What are the capacities? You can determine the quantity of allotments while making a RDD either by utilizing the sc.textFile or by utilizing parallelize works as pursues: Val rdd = sc.parallelize(data,4) val information = sc.textFile(“path”,4) 7. What are activities and changes? Changes make new RDD’s from existing RDD and these changes are sluggish and won’t be executed until you call any activity. Example:: map(), channel(), flatMap(), and so forth., Activities will return consequences of a RDD. Example:: lessen(), tally(), gather(), and so on., 8. What is Lazy Evaluation? On the off chance that you make any RDD from a current RDD that is called as change and except if you consider an activity your RDD won’t be emerged the reason is Spark will defer the outcome until you truly need the outcome in light of the fact that there could be a few circumstances you have composed something and it turned out badly and again you need to address it in an intuitive manner it will expand the time and it will make un-essential postponements. Additionally, Spark improves the required figurings and takes clever choices which is beyond the realm of imagination with line by line code execution. Sparkle recoups from disappointments and moderate laborers. 9. Notice a few Transformations and Actions Changes map (), channel(), flatMap() Activities diminish(), tally(), gather() 10. What is the job of store() and continue()? At whatever point you need to store a RDD into memory with the end goal that the RDD will be utilized on different occasions or that RDD may have made after loads of complex preparing in those circumstances, you can exploit Cache or Persist. You can make a RDD to be continued utilizing the persevere() or store() works on it. The first occasion when it is processed in an activity, it will be kept in memory on the hubs. When you call persevere(), you can indicate that you need to store the RDD on the plate or in the memory or both. On the off chance that it is in-memory, regardless of whether it ought to be put away in serialized organization or de-serialized position, you can characterize every one of those things. reserve() resembles endure() work just, where the capacity level is set to memory as it were.

11. What are Accumulators? Collectors are the compose just factors which are introduced once and sent to the specialists. These specialists will refresh dependent on the rationale composed and sent back to the driver which will total or process dependent on the rationale. No one but driver can get to the collector’s esteem. For assignments, Accumulators are compose as it were. For instance, it is utilized to include the number blunders seen in RDD crosswise over laborers. 12. What are Broadcast Variables? Communicate Variables are the perused just shared factors. Assume, there is a lot of information which may must be utilized on various occasions in the laborers at various stages. 13. What are the enhancements that engineer can make while working with flash? Flash is memory serious, whatever you do it does in memory. Initially, you can alter to what extent flash will hold up before it times out on every one of the periods of information region information neigh borhood process nearby hub nearby rack neighborhood Any. Channel out information as ahead of schedule as could be allowed. For reserving, pick carefully from different capacity levels. Tune the quantity of parcels in sparkle. 14. What is Spark SQL? Flash SQL is a module for organized information handling where we exploit SQL questions running on the datasets. 15. What is a Data Frame? An information casing resembles a table, it got some named sections which composed into segments. You can make an information outline from a document or from tables in hive, outside databases SQL or NoSQL or existing RDD’s. It is practically equivalent to a table. 16. How might you associate Hive to Spark SQL? The principal significant thing is that you need to place hive-site.xml record in conf index of Spark. At that point with the assistance of Spark session object we can develop an information outline as, 17. What is GraphX? Ordinarily you need to process the information as charts, since you need to do some examination on it. It endeavors to perform Graph calculation in Spark in which information is available in documents or in RDD’s. GraphX is based on the highest point of Spark center, so it has got every one of the abilities of Apache Spark like adaptation to internal failure, scaling and there are numerous inbuilt chart calculations too. GraphX binds together ETL, exploratory investigation and iterative diagram calculation inside a solitary framework. You can see indistinguishable information from the two charts and accumulations, change and unite diagrams with RDD effectively and compose custom iterative calculations utilizing the pregel API. GraphX contends on execution with the quickest diagram frameworks while holding Spark’s adaptability, adaptation to internal failure and convenience. 18. What is PageRank Algorithm? One of the calculation in GraphX is PageRank calculation. Pagerank measures the significance of every vertex in a diagram accepting an edge from u to v speaks to a supports of v’s significance by u. For exmaple, in Twitter if a twitter client is trailed by numerous different clients, that specific will be positioned exceptionally. GraphX accompanies static and dynamic executions of pageRank as techniques on the pageRank object. 19. What is Spark Streaming? At whatever point there is information streaming constantly and you need to process the information as right on time as could reasonably be expected, all things considered you can exploit Spark Streaming. 20. What is Sliding Window? In Spark Streaming, you need to determine the clump interim. In any case, with Sliding Window, you can indicate what number of last clumps must be handled. In the beneath screen shot, you can see that you can indicate the clump interim and what number of bunches you need to process. 21. Clarify the key highlights of Apache Spark. Coming up next are the key highlights of Apache Spark: Polyglot Speed Multiple Format Support Lazy Evaluation Real Time Computation Hadoop Integration Machine Learning 22. What is YARN? Like Hadoop, YARN is one of the key highlights in Spark, giving a focal and asset the executives stage to convey adaptable activities over the bunch. YARN is a conveyed holder chief, as Mesos for instance, while Spark is an information preparing instrument. Sparkle can keep running on YARN, a similar way Hadoop Map Reduce can keep running on YARN. Running Spark on YARN requires a double dispersion of Spark as based on YARN support. 23. Do you have to introduce Spark on all hubs of YARN bunch? No, in light of the fact that Spark keeps running over YARN. Flash runs autonomously from its establishment. Sparkle has a few alternatives to utilize YARN when dispatching employments to the group, as opposed to its very own inherent supervisor, or Mesos. Further, there are a few arrangements to run YARN. They incorporate ace, convey mode, driver-memory, agent memory, agent centers, and line. 24. Name the parts of Spark Ecosystem. Spark Core: Base motor for huge scale parallel and disseminated information handling Spark Streaming: Used for handling constant spilling information Spark SQL: Integrates social handling with Spark’s useful programming API GraphX: Graphs and chart parallel calculation MLlib: Performs AI in Apache Spark 25. How is Streaming executed in Spark? Clarify with precedents. Sparkle Streaming is utilized for handling constant gushing information. Along these lines it is a helpful expansion deeply Spark API. It empowers high-throughput and shortcoming tolerant stream handling of live information streams. The crucial stream unit is DStream which is fundamentally a progression of RDDs (Resilient Distributed Datasets) to process the constant information. The information from various sources like Flume, HDFS is spilled lastly handled to document frameworks, live dashboards and databases. It is like bunch preparing as the information is partitioned into streams like clusters. 26. How is AI executed in Spark? MLlib is adaptable AI library given by Spark. It goes for making AI simple and adaptable with normal learning calculations and use cases like bunching, relapse separating, dimensional decrease, and alike. 27. What record frameworks does Spark support? The accompanying three document frameworks are upheld by Spark: Hadoop Distributed File System (HDFS). Local File framework. Amazon S3 28. What is Spark Executor? At the point when SparkContext associates with a group chief, it obtains an Executor on hubs in the bunch. Representatives are Spark forms that run controls and store the information on the laborer hub. The last assignments by SparkContext are moved to agents for their execution. 29. Name kinds of Cluster Managers in Spark. The Spark system underpins three noteworthy sorts of Cluster Managers: Standalone: An essential administrator to set up a group. Apache Mesos: Generalized/regularly utilized group administrator, additionally runs Hadoop MapReduce and different applications. YARN: Responsible for asset the board in Hadoop. 30. Show some utilization situations where Spark beats Hadoop in preparing. Sensor Data Processing: Apache Spark’s “In-memory” figuring works best here, as information is recovered and joined from various sources. Real Time Processing: Spark is favored over Hadoop for constant questioning of information. for example Securities exchange Analysis, Banking, Healthcare, Telecommunications, and so on. Stream Processing: For preparing logs and identifying cheats in live streams for cautions, Apache Spark is the best arrangement. Big Data Processing: Spark runs upto multiple times quicker than Hadoop with regards to preparing medium and enormous estimated datasets. 31. By what method can Spark be associated with Apache Mesos? To associate Spark with Mesos: Configure the sparkle driver program to associate with Mesos. Spark paired bundle ought to be in an area open by Mesos. Install Apache Spark in a similar area as that of Apache Mesos and design the property ‘spark.mesos.executor.home’ to point to the area where it is introduced. 32. How is Spark SQL not the same as HQL and SQL? Flash SQL is a unique segment on the Spark Core motor that supports SQL and Hive Query Language without changing any sentence structure. It is conceivable to join SQL table and HQL table to Spark SQL. 33. What is ancestry in Spark? How adaptation to internal failure is accomplished in Spark utilizing Lineage Graph? At whatever point a progression of changes are performed on a RDD, they are not assessed promptly, however languidly. At the point when another RDD has been made from a current RDD every one of the conditions between the RDDs will be signed in a diagram. This chart is known as the ancestry diagram. Consider the underneath situation Ancestry chart of every one of these activities resembles: First RDD Second RDD (applying map) Third RDD (applying channel) Fourth RDD (applying check) This heredity diagram will be helpful on the off chance that if any of the segments of information is lost. Need to set spark.logLineage to consistent with empower the Rdd.toDebugString() gets empowered to print the chart logs. 34. What is the contrast between RDD , DataFrame and DataSets? RDD : It is the structure square of Spark. All Dataframes or Dataset is inside RDDs. It is lethargically assessed permanent gathering objects RDDS can be effectively reserved if a similar arrangement of information should be recomputed. DataFrame : Gives the construction see ( lines and segments ). It tends to be thought as a table in a database. Like RDD even dataframe is sluggishly assessed. It offers colossal execution due to a.) Custom Memory Management – Data is put away in off load memory in twofold arrangement .No refuse accumulation because of this. Optimized Execution Plan – Query plans are made utilizing Catalyst analyzer. DataFrame Limitations : Compile Time wellbeing , i.e no control of information is conceivable when the structure isn’t known. DataSet : Expansion of DataFrame DataSet Feautures – Provides best encoding component and not at all like information edges supports arrange time security. 35. What is DStream? Discretized Stream (DStream) Apache Spark Discretized Stream is a gathering of RDDS in grouping . Essentially, it speaks to a flood of information or gathering of Rdds separated into little clusters. In addition, DStreams are based on Spark RDDs, Spark’s center information reflection. It likewise enables Streaming to flawlessly coordinate with some other Apache Spark segments. For example, Spark MLlib and Spark SQL. 36. What is the connection between Job, Task, Stage ? Errand An errand is a unit of work that is sent to the agent. Each stage has some assignment, one undertaking for every segment. The Same assignment is done over various segments of RDD. Occupation The activity is parallel calculation comprising of numerous undertakings that get produced in light of activities in Apache Spark. Stage Each activity gets isolated into littler arrangements of assignments considered stages that rely upon one another. Stages are named computational limits. All calculation is impossible in single stage. It is accomplished over numerous stages. 37. Clarify quickly about the parts of Spark Architecture? Flash Driver: The Spark driver is the procedure running the sparkle setting . This driver is in charge of changing over the application to a guided diagram of individual strides to execute on the bunch. There is one driver for each application. 38. How might you limit information moves when working with Spark? The different manners by which information moves can be limited when working with Apache Spark are: Communicate and Accumilator factors 39. When running Spark applications, is it important to introduce Spark on every one of the hubs of YARN group? Flash need not be introduced when running a vocation under YARN or Mesos in light of the fact that Spark can execute over YARN or Mesos bunches without influencing any change to the group. 40. Which one will you decide for an undertaking – Hadoop MapReduce or Apache Spark? The response to this inquiry relies upon the given undertaking situation – as it is realized that Spark utilizes memory rather than system and plate I/O. In any case, Spark utilizes enormous measure of RAM and requires devoted machine to create viable outcomes. So the choice to utilize Hadoop or Spark changes powerfully with the necessities of the venture and spending plan of the association. 41. What is the distinction among continue() and store() endure () enables the client to determine the capacity level while reserve () utilizes the default stockpiling level. 42. What are the different dimensions of constancy in Apache Spark? Apache Spark naturally endures the mediator information from different mix tasks, anyway it is regularly proposed that clients call persevere () technique on the RDD on the off chance that they intend to reuse it. Sparkle has different tirelessness levels to store the RDDs on circle or in memory or as a mix of both with various replication levels. 43. What are the disservices of utilizing Apache Spark over Hadoop MapReduce? Apache Spark’s in-memory ability now and again comes a noteworthy barrier for cost effective preparing of huge information. Likewise, Spark has its own record the board framework and consequently should be incorporated with other cloud based information stages or apache hadoop. 44. What is the upside of Spark apathetic assessment? Apache Spark utilizes sluggish assessment all together the advantages: Apply Transformations tasks on RDD or “stacking information into RDD” isn’t executed quickly until it sees an activity. Changes on RDDs and putting away information in RDD are languidly assessed. Assets will be used in a superior manner if Spark utilizes sluggish assessment. Lazy assessment advances the plate and memory utilization in Spark. The activities are activated just when the information is required. It diminishes overhead. 45. What are advantages of Spark over MapReduce? Because of the accessibility of in-memory handling, Spark executes the preparing around 10 to multiple times quicker than Hadoop MapReduce while MapReduce utilizes diligence stockpiling for any of the information handling errands. Dissimilar to Hadoop, Spark gives inbuilt libraries to play out numerous errands from a similar center like cluster preparing, Steaming, Machine learning, Interactive SQL inquiries. Be that as it may, Hadoop just backings cluster handling. Hadoop is very plate subordinate while Spark advances reserving and in-memory information stockpiling. 46. How DAG functions in Spark? At the point when an Action is approached Spark RDD at an abnormal state, Spark presents the heredity chart to the DAG Scheduler. Activities are separated into phases of the errand in the DAG Scheduler. A phase contains errand dependent on the parcel of the info information. The DAG scheduler pipelines administrators together. It dispatches task through group chief. The conditions of stages are obscure to the errand scheduler.The Workers execute the undertaking on the slave. 47. What is the hugeness of Sliding Window task? Sliding Window controls transmission of information bundles between different PC systems. Sparkle Streaming library gives windowed calculations where the changes on RDDs are connected over a sliding window of information. At whatever point the window slides, the RDDs that fall inside the specific window are consolidated and worked upon to create new RDDs of the windowed DStream. 48. What are communicated and Accumilators? Communicate variable: On the off chance that we have an enormous dataset, rather than moving a duplicate of informational collection for each assignment, we can utilize a communicate variable which can be replicated to every hub at one timeand share similar information for each errand in that hub. Communicate variable assistance to give a huge informational collection to every hub. Collector: Flash capacities utilized factors characterized in the driver program and nearby replicated of factors will be produced. Aggregator are shared factors which help to refresh factors in parallel during execution and offer the outcomes from specialists to the driver. 49. What are activities ? An activity helps in bringing back the information from RDD to the nearby machine. An activity’s execution is the aftereffect of all recently made changes. lessen() is an activity that executes the capacity passed over and over until one esteem assuming left. take() move makes every one of the qualities from RDD to nearby hub. 50. Name kinds of Cluster Managers in Spark. The Spark system bolsters three noteworthy kinds of Cluster Managers: Independent : An essential administrator to set up a bunch. Apache Mesos : Summed up/ordinarily utilized group director, additionally runs Hadoop MapReduce and different applications. PYSPARK Questions and Answers Pdf Download Read the full article

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