#Large Table Indexing Strategies

[thedbahub]

Utilization and Performance Evaluation of HierarchyId in SQL Server

In the intricate world of database management, navigating through hierarchical data like organizational charts or product categories poses a significant challenge. SQL Server steps up with the HierarchyId data type, a nifty CLR (Common Language Runtime) feature, tailor-made for those looking to streamline the storage and querying of hierarchical information. We’re about to take a deep dive into…

[memethebum]

Finally got another fluffy lil oneshot out!!

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Soul knew his life would change in a few substantial ways after their battle against Asura on the moon.

He’d expected to have an absolute awful time going about certain changes, but had ultimately found that the most annoying part of using his familial surname and being named the last Deathscythe was really just having to remind people that Maka was the one that’d honed him into reaching his full potential thank you very much and being very vocal about having no real desire to play in front of anyone for the time being.

The rest of his life was left relatively unchanged, which meant that most his days were filled with finishing his classes or cleaning up the cuts and bruises both he and his meister had earned through the missions they were assigned.

However, what he wasn’t prepared for were the last few hurdles that came before he and his peers would finally be able to graduate.

He’d tried not to let out an audible groan when Sid and Stein had announced that their super final exam would be graded by combining the scores of both the meister and weapon in a pair, causing him to look over his shoulder and feel his blood immediately run cold once noticing the fiery look in Maka’s emerald eyes.

The decision had ultimately left his final weeks of school as a boot camp for raising his C student status into a A- status at the very least in order to appease his obstinate meister.

“One more day and then I’m fuckin’ free,” Soul had mumbled into Maka’s pillow cover the night before the exam as Maka flipped through the pages of a study book she’d bought during the beginning of the school year.

He’d expected her to let out a small giggle or simply give him a sarcastic eye roll but had been met with a mischievous smile once she raised her head from the textbook to gaze into his scarlet eyes.

“I think I know a way to make this more exciting…” Maka then exclaimed as Soul watched her reach over towards her bedside table and fumble her hand around before eventually retrieving a stick of chapstick Liz had bought him after exclaiming he needed to delve into some extra measures to please the missus.

“Oh really? Does it involve more flashcards?” Soul snorted back while watching his meister pull the cap off the stick of chapstick and gingerly swipe the honey scented wax over her lips.

“Nope. It’s much simpler than that…” Maka hummed, probing Soul to prop himself up on one of his elbows and let out a simple ohh in response to her statement.

“I’ll give you a kiss for every question you get right on the study guide,” Maka then finished before Soul raised his eyebrows at the offer as he watched his girlfriend run one of her fingers over her tantalizing lips.

I hate how good of a strategy that is… Soul then thought while his vision trickled down towards Maka’s lips once more, which only heightened his thoughts about how feeling her lips against his own seemed to be a high his years of unrelenting pining could’ve never done justice to.

“I gotta deal with memorizing 30 pages of notes and now I’ve gotta earn a kiss from my girlfriend? You’re really trynna’ kill me this weekend, huh?” Soul replied with a faux groan of agony before Maka slid open her bedside drawer and flung a thick pile of flashcards onto her bed.

“If you don’t like that idea, we could always practice with these,” the young woman replied while using one of her fingers to toy with the large rubber band that kept the index cards in a neat and imposing stack.

“I’m jokin’, I’m jokin. Let’s play your lil’ game,” Soul then murmured before watching Maka’s lips turn into a grin while she shimmied herself across her smooth mattress until she was snug against his chest.

“Ok…let’s start with an easy one. Name a famous inventor that shaped Shibusen’s academic structure,” Maka questioned as she buried her face closer towards Soul’s chest, causing him to let out a giggle.

“That’s a lil’ too easy. Eibon, duh…” the Deathscythe exclaimed before noticing Maka angle her head upwards until the taste of wax and honey glided across the right corner of his lips.

“Good job! I guess we can move on to something more challenging. Hmm, how many countries engage in student referrals for Shibusen?” the young woman then hummed while gazing back down at her study book, leaving Soul to gingerly slide his fingers across her flaxen strands of hair.

“400,” the young man replied before feeling Maka place a quick peck onto his nose.

“You finally got that one right,” Maka beamed, only to slot her lips against Soul’s before he could even give her a witty response.

“Mmm, ok question three…” his girlfriend then huffed out as he prepared himself to keep sifting through the plethora of information she’d shoved into his cranium over the week.

“What’s the acronym that describes the proper way to dispose of a pre-kishin soul?” Maka read aloud, forcing Soul to let out a grunt as his concentration seemed to diminish the more he thought about the question.

Fuck, I don’t remember that bein’ on the study guide… Soul mentally noted while watching Maka’s lips turn into a pout at his lack of an immediate answer.

“I dunno’ Earn.A.Treat or somethin’?” the Deathscythe coughed out before Maka shook her head and then shuffled one of her hands through the stack of flashcards laying on the edge of her bed.

“Nope, it’s Absorb.Or.Supervise, so AOS for short,” Maka added as Soul gently reached down and traced his thumb across one of her cheekbones.

“I don’t suppose I could get a free kiss for that one, considerin’ it wasn’t on the study guide?” the Deathscythe probed, earning him a chuckle from Maka before he felt her plop the stack of flashcards onto his lap.

“It might’ve not been on the study guide, but it was definitely in the flashcards, so no kisses for you,” Maka tittered, eliciting Soul to let out a groan and pry the textbook out of her hands.

“Oh yea, if you’re so sure of yourself why don’t I quiz ya’ instead?” Soul grumbled, knowing full well that Maka had not only memorized all of the flashcards in that insufferable stack she’d compiled but had also reread their textbook at least three times by now in hopes of earning a perfect score for their final test.

The Deathscythe then watched as Maka’s eyebrows furrowed at the question, only for his face to morph into a devious grin once she shrugged her shoulders at him.

“Try me…” his girlfriend responded before Soul let out a low chuckle at how easily she had taken the bait.

I wonder if she knows I’m cheatin’ the system.. the Deathscythe mentally noted while flipping through Maka’s study book and ultimately landing his eyes on a set of questions sprawled on the page.

Eh, doesn’t matter which one I choose. It’s all gonna lead to the same thing…

“Alright, question one. Which continent has the greatest population of individuals with a sword transformation gene?” Soul questioned before feeling Maka rest her head against his midriff and release a languid hum.

“Europe,” the young woman immediately responded, probing Soul to let out a jubilant chuckle as he reached down and placed a small peck against the crook of her neck.

“Question two. Name a famous individual who had once been a meister for Shibusen,” the young man then mumbled into Maka’s neck, only to feel her swat a hand against his head a moment afterwards.

“Ugh, you could at least check the study book to see if the first one was right. As for the second one, I’m gonna go with Albert Einstein,” Maka added, causing Soul to release a quick chuckle before placing a chaste kiss onto her jaw.

“Why would I need to check the book when I’ve got the smartest girlfriend in the universe?” the Deathscythe sang in between a quick peck onto the back of Maka’s palm and then her wrist.

“Mmmm you’re just using this as an excuse to get more kisses, aren’t you,” Maka replied before Soul felt the warmth of her palms smack against the sides of his face, serving as his sign to look down and notice her mildly irked expression.

“Ok ok last question,” Soul breathed out while feeling his girlfriend’s fingers begin to slide away from his stubbled chin as he rested his forehead against her own.

“Who’s gonna get a perfect score tommorow?” the young man rumbled out before feeling his heart begin to skip a few beats as Maka giggled against his touch.

“We are,” his girlfriend exclaimed before catching his lips on her own once more, although this time she’d decided to step things up another level by sliding a firm hand onto the back of Soul’s head as she gasped between their lips moving against one another.

It didn’t take long for Soul to notice that they’d somehow become tangled in a pile of limbs and needy hands ontop Maka’s satin bedsheets, causing him to let out another groan while his girlfriend nibbled on his lower lip before sighing against him once they both decided to pull away.

The Deathscythe could feel his breathing begin to even out while Maka nuzzled herself into the crook of his neck, allowing him to stretch out his arm in order to wrap it across her shoulder and hold them snug together.

“I’m gonna miss this…” Maka eventually murmured, probing Soul to dip his head down in order to lay his chin ontop of her scalp and let out a hmmm in confusion.

“Y’know, just having enough free time to relax like this. Papa was pretty busy as Lord Death’s Deathscythe, so you’re probably going to be pretty busy being Kid’s weapon-“

“Hey hey, it’s gonna be ok,” Soul hummed over the young woman as he felt her fingers scratch against the loose fabric of his t-shirt with every word she’d uttered out.

“Me n’ Kid both decided that I’d just be his personal prop if we partnered up, so I’d only be needed for special events. Plus, I think Liz would come after my ass if I just took her and Patty’s job like that,” Soul giggled out while he pushed a few of Maka’s sleek bangs aside in order to have a clear view of her cool emerald eyes shooting up to gaze at him.

“You…really mean all that? You’re not just saying it to make me feel better, right? Maka then questioned, eliciting Soul to fidget his arms around until he could gently fit his fingers between each of Maka’s knuckles.

“Course’ not. Our partnership is the most important thing to me, Maka. And besides, I said I’d follow ya’ to the ends of the earth, didn’t I?”

[wordywarriorwrites]

Trouble

A03 | Pairing: Dave York x OFC | Rating: M

Warnings: Mentions of violence. Language. Smut. Angst.

Summary: Dave's in hiding and always on the move. He knows better than to allow himself to be drawn in, but this time, he just can't help it.

A/N: For @yxtkiwiyxt's Never Have I Ever Challenge. Also, "Trouble" by Ray LaMontagne played repeatedly in my head while writing this.

A tiny café in Podunk town, with only two tables and no security camera. Their version of a morning rush (ten patrons – six women, four men) had come and gone an hour ago. Dave people-watched, mentally mapped out exit strategies, and sized up items he could use as weapons.

But he hadn’t prepared himself for her.

Black shoes, black pants, and a purple sweater. Dark hair and dark eyes. A lemon poppyseed muffin and a steaming cup three times the size he had in his hand. His mind calculated her. Assessed her. Turned her over until he concluded she was simply a late arrival and posed no threat.

“May I?” she asked, index finger pointed toward the empty chair across from him.

Dave knew what he looked like – unshaven, with threadbare clothes, unkempt hair, and an overgrown beard. He no longer bothered with the eyepatch because he was badly scared and had grown weary of trying to hide it for the comfort of others. He was clean but wanted to appear haphazard and unapproachable, and most people – especially women – averted their gaze or looked right through him, which was how he preferred it.

The other table, situated beneath a large, overly blurred poster of a coffee bean, had been taken up by a middle-aged woman with a cellphone that she was manically glued to. He'd gotten a brief glimpse of the screen and knew the lady’s poison was online slots. Addicts were everywhere, even in small towns, and her wild eyes indicated that she had zero intention of leaving the only place other than the library that offered free Wi-Fi.

“That’s Veronica,” she whispered gently. “She’s… Well, she’s struggling.”

Between the choice of sitting with him or the twitchy gambler, this woman seemed to find him the lesser of two evils. Dave wasn’t flattered or insulted by it. He could’ve left – just vacated his seat, taken his overpriced java and too-dry hunk of banana bread, and walked right out the door. He could’ve gotten back into his shitty car and kept on down the road, but he didn’t.

Instead, he looked up at her, and when he met her eyes, he realized the mistake in his assessment. She wouldn’t slit his throat – that much he was confident about – but she was trouble of a different kind, and something about her made a synapse fire in his brain. Dave hadn’t meant to nod because even the most innocuous things, like sharing a table with a stranger, could cause problems.

But then, she smiled, and that was that.

A nondescript Toyota, with a false VIN and fake plates – that was Dave’s home and mode of transportation. A flat tire should’ve been relatively easy to deal with, but he couldn’t get the damn thing off with the tools he had on hand. Being trapped had thrown him into an even higher plane of hypervigilance, and though several people had slowed down and offered to help him, he’d either ignored or refused them.

Then, she arrived.

Her vehicle – a dark green truck with an open bed and flashing hazard lights – slowed to a stop right next to his. There hadn’t been a polite offer for Dave to refuse or disregard because she hadn’t bothered with one. She simply climbed down from her truck, snagged her toolbox from the back, and joined him on the side of the road.

“Well,” she sighed as she rolled up the sleeves of her maroon-colored hoodie and crouched beside him. “Looks like you’ve damaged your nuts.”

In the past, he would have laughed and maybe even engaged in some light banter. But this wasn’t the past, and he wasn’t amused.

The silence that followed was broken only by an occasional car passing by. Her bolt extractor and hammer, his brute strength and stubbornness – a winning combination that saw the flat removed and the equally pitiful spare put into place.

She stood tall and wiped her hands on her dark blue jeans, “You’re going bald.”

Dave grunted and packed up the toolbox. The flat went into the trunk, and out of the corner of his eye, he saw her gesture with a pointed toe encased in a leather loafer toward his back passenger tire. It should’ve been replaced thousands of miles ago, but he kept that to himself. He kept all his thoughts to himself and slammed the trunk shut.

If she thought him rude, she didn’t show it; she just recommended a shop a couple of blocks over that would give him a fair price on a set if he was interested.

He quirked a brow.

She retrieved her toolbox, waved, and took off without a backward glance.

Dave no longer had the pretty face he once had, nor did he have access to CIA-level tech, but he still could learn things about people when he put his mind to it.

He found out her name. Discovered she was the town’s resident bookkeeper, and she worked from home. Was informed that she preferred appointments, but also took walk-ins, and her standard order at the café was a triple-shot espresso.

And chestnut brown, Dave decided, was the color of her hair.

A small, one-story brick house on the end of Corduroy Lane, with an antique-looking business sign in the front yard that listed her services and credentials. A solitary concrete step that led up to a stoop too small to be classified as a porch. A bright red door. A brass claddagh knocker.

The last notes of the bell had just faded when she answered, dressed in black slacks and a pale green button down, face fixed into a professional expression. A practiced exterior that faded quickly, followed by a pleasant greeting and a smile – neither of which he returned. Instead, he held the coffee he’d purchased for her aloft and gestured for her to take it.  

She accepted it with a small nod, and as she sipped, Dave thought what an easy target she’d make.

A single woman who worked alone and most likely lived alone. The kind of woman who invited strangers into her home, trusting they wouldn’t hurt her as she poured over their financials and unwittingly learned all their dirty, little secrets. The type of woman who sat at tables with men she didn’t know, who stopped and helped them change flat tires and accepted coffee from them. A woman ignorant to the danger that could reach out and grab her at any time… 

“Do you like pizza?” she wondered.

Dave blinked. Nodded.

“Fiona’s - the bar around the corner - makes a good pie.”

That smile of hers appeared again. A car door slammed shut.

“Sorry to cut this short, but my next appointment is here,” she announced, eyes momentarily pulled to the delicate timepiece on her right wrist before returning to him. “Thanks for the coffee.”

Dave may have shrugged. He might not have. All he knew as he headed back down the sidewalk toward his car with its’ four brand-new tires that had depleted nearly all his savings was that she needed a better deadbolt for her front door.

By the time Dave arrived at the bar, she was already two slices into an extra-large meat lovers, and the pint of beer she’d ordered was half-empty.  

A high back stool with legs that wobbled like a newborn foal. Tomato sauce and oregano and maraschino cherries. A stereo that blasted Guns and Roses fought for dominance with a flat screen that had been turned on to the ballgame. A neon Coors Light sign. A sticky floor that made his boots squeak with every step.

“Beer?” she offered.

He nodded, and a few moments later, the bartender slid him a pint of whatever was on draft with an acceptably foamy head. While he settled in, she grabbed a handful of napkins from the pile by her elbow and dropped several slices onto a paper plate.

“Place is a shithole,” she declared as she placed the napkins and plate in front of him.  “But the beer is cold, and the pizza is good.”

Five pieces later, Dave agreed, and her unassuming presence, combined with nobody else joining them at the bar, helped keep his shoulders from crawling up into his earlobes. It was a lot for him – the noise, the smells, the people, the terrible lighting, but seated next to her…

“Diner up the street has fish fry on Fridays,” she voiced. She dipped her crust in a little plastic cup of ranch and shrugged as she brought it to her mouth. “Maybe I’ll see you there.”

Dave sat back. Ran a napkin over his mouth. Her profile was soft. Her ears were pierced, but unadorned, and she had a freckle about an inch from her lateral canthus. The high-waisted bellbottoms and buttercup yellow sweater made her look warm. Approachable.

As she chewed, he tried to find something – anything, really – to explain why the hell a good-looking woman like her would bother to give a man like him the time of day. He’d been trained to sniff out subterfuge and knew exactly what pity looked and sounded like, but he could sense none of that.

He finished his beer. The bartender refilled it.

“Fridays?” Dave muttered.

“Fridays,” she replied.   

He nodded. She saluted him with her own refilled glass.

Dave met up with her at the diner on Friday.

Stupid, really, to allow himself to become entangled with her. A risk, too, because of her standing in the town and his unfortunate-looking face. People liked her. Knew her by name. The waitress who brought the menus and silverware covered in water spots eyeballed him hard, and Dave should’ve cared about that, but he hadn’t given a damn.

Because he was uncharacteristically horny. And suddenly starved for attention. Her attention. 

Pathetic.  

“I’ve never broken a bone,” she stated absentmindedly.   

The booth across from them was crammed with high school kids in nearly identical letterman jackets. One boy, maybe sixteen, was seated on the outside, leg outstretched to accommodate a rather large, neon-pink cast. The large “C” on his chest indicated he was the boss of the bunch, and the way the others sucked up to him confirmed it.

Dave had already clocked the rowdy group and the crutches against the wall when he walked in, but still, he followed her gaze until it returned to him. She popped a fry into her mouth and chewed politely while she seemed to consider him.

“Have you?” she eventually wondered as she reached for her drink.

The ice rattled as the straw passed her lips, and the thought of her mouth and all its unknown capabilities burned through him like a shot. Dave imagined how sweet her cola-coated tongue would taste. How nice it would feel wrapped around his cock. He wondered if she’d swallow.

Embarrassed and ashamed, he cleared his throat and looked away. The waitress chose that moment to return and glare at him some more, which he inwardly admitted he deserved. Outwardly, he ignored her. Refills, extra napkins, and more tartar sauce – the topics covered gave him time to compose himself, and when they were alone again, she prodded once more.

“Several,” Dave finally answered.

“Bad accident?”

“Pushed off a cliff.”

She paused mid-squeeze on a lemon wedge, but her eyes never wavered. Even when the waitress came back with their requested items, she didn’t look away. Even when the bell above the door chimed and announced the arrival of more customers, her stare remained focused.

Two toddlers in the booth behind him had been jumping up and down and singing the same refrain of Wheels on the Bus for a solid fifteen minutes. The couple seated behind her had been arguing over everything from the cable bill to the acceptable amount of pepper one should put on mashed potatoes. Someone dropped a plate, and the sound of shattered ceramic momentarily sucked all the noise and levity from the room.

Still, she hadn’t flinched.

Dave had told so many lies about his scars that it had become impossible to remember them all. Even the doctors and nurses who’d saved his life never learned the full details of what happened. She was the only person he’d ever told the truth to, and the unintended admission had somehow made the burden he carried feel less heavy – like simply telling her, even without the gory details, had halved the weight somehow.

Chaos resumed quickly, but the tension remained and stifled the little conversation they’d been having. Eventually, she transferred her purse to her lap and outed two twenties. Crisp, clean, and not at all like the bills he had wadded up in his pocket, she placed them next to her plate and polished off her soda.

The strap of her bag was thin, with a shiny silver buckle, and it slipped over the round of her shoulder without any fuss. When she scooted out of the booth, Dave followed suit, and the narrow, cramped space of the aisle put him in the closest proximity he’d been to a human being since his brush with death.

“I like you,” she asserted.

He stared down at her, “That’s unfortunate.”

Brow furrowed, she turned and headed toward the door. Dave followed her and silently admired her form as she stepped out of the restaurant and into the parking lot. He knew her truck was parked close to the building, which he thought was very sensible, and he escorted her to it.

She outed her keys, “Ever slept with someone on the first date?”

“No,” he answered.

“Me neither,” she admitted. "But I want to. With you."

Once the locks were disengaged, Dave reached for the handle and opened the door for her.

“This wasn’t a date,” he said.

She sighed, “You sure about that?"

It had been two weeks since fish fry Friday.

Well, thirteen days and sixteen hours, to be precise.

Dave’s primary focus had become getting out of town, which he needed money for – a few hundred, at least, if he wanted to put some real distance between himself and this woman who’d started to preoccupy his thoughts entirely too much.

Luckily for him, the town had enough small business owners who supported veterans. Once he’d told them his injuries were war-related, and that it had been hard for him to find steady work, they’d been all too eager to let him do odd jobs in exchange for cash. He was a liar, yes, but not a thief, and it would take a few more days – maybe a week – but only if he stayed focused.

It was Thursday. The clock on the dash signaled it was nearly midnight. He’d just gotten to his preferred parking space – a spot behind the animal shelter that offered direct escape routes, good coverage, and lighting that allowed him to see anything that might come at him.

There was another, smaller lot behind the grocery store, but he only parked there on nights when he couldn’t sleep. Tonight, he was tired. So, he parked at the shelter. And perhaps if he hadn’t been so tired, so focused on getting the hell out of town, on getting the hell away from her, he would’ve noticed her truck when he pulled in.

She emerged from the back door, bag of trash in hand. Head on a swivel, she scanned the lot as she marched toward the dumpster. She opened the lid. Tossed the bag inside. Dave stupidly held his breath, as if that would somehow prevent her from seeing him, but she knew his car.

As soon as she spotted him, she stopped.

Dave had a half tank of gas. The key was still in the ignition. But his treacherous hand went for the door handle instead. The hinges squeaked loudly, and as he slowly climbed out, she crept forward, until she’d moved out of the light and into the shadows with him.

“I volunteer here,” she said.

“I park here,” he replied.

She nodded. Shoved her hands into her pockets. Told him she’d made lasagna, if he was interested in that sort of thing, and headed back inside.

Twenty minutes later, when her truck eased onto the street, he followed.

Dave recalled washing his hands at the kitchen sink. He ate three servings of lasagna. Drank several glasses of water. Whatever happened after he helped clean up was lost on him because, like a fade-to-black moment in a movie, his mind blanked.

When he came back online, it was to the scent of dark roast and sunlight. Other details trickled in slowly, like the too-small couch and the ache in his lower back. The soft blanket draped over him and the pillow tucked beneath his head. Belt and boots off. Shirt and pants on. Big toe stuck out of the hole in the seam of his sock.

He sat up. Wiped the sleep from his eyes. When he looked around, he spotted her in the kitchen, robe donned and steaming mug in hand.

“You snore,” she voiced.

He grunted. Stretched. Got to his feet.

“Bathroom?” he yawned out.

She gestured toward a slightly ajar door with her mug. After Dave finished and stepped back into the living room, he looked around her home and took in all the minuscule details he’d only briefly glossed over the night before. Like the shearling rug beneath his feet, the candles on the coffee table, and the small television in the corner. Books. Magazines. A coat-and-shoe-rack combo with seasonal attire and several pairs of well-worn shoes. A fish tank without any fish. Gauzy curtains, creaky hardwood floors, and an antique mechanical calculator.

A pair of double doors with frosted windows – that’s what separated her personal and professional lives. A neat-as-a-pin space, with carefully situated office furniture, fake plants, and tall floor lamps. The desk was also tidy – just a laptop, a box of tissues, and a pen holder. There was a small filing cabinet within arm’s reach, a framed degree on the wall, and a sideboard with a Keurig.

A contradiction of spaces – one he took in the source and reason of when his eyes finally stopped ping-ponging and returned to her. Adorned in a clownfish orange robe and holding an obscenely large cup with the phrase Save the Whales on it. A bruise on her shin and toenails painted a deep berry color. Her hair glowed in the sunlight, and when she turned and opened the cabinet nearest her, the hinge squeaked.

“Name’s Dave,” he confessed to her back. 

She stilled for a moment. Then, both mugs were carefully placed on the counter. She didn’t say anything – just turned her head slightly, revealing the slope of her nose, the apple of her cheek, and the barest, upturned corner of her mouth.

A few footsteps – that’s all that existed between him and her, and he shortened the distance until his hands could reach the frayed fabric of her robe. The rounds of her shoulders fit perfectly in his palms, and her hips filled his grip when he squeezed them. The robe had been worn in, made softer by repeated washing and wearing, but it was nothing compared to her skin. A tiny sliver of it was revealed to his eyes and touch because there was a tear the size of his thumb just above the belt around her waist, and it was enough to make him ache.

“What do you want, Dave?”  

"You," he admitted, eyes trained on the flutter of her lashes.

She let out a ragged breath, “Okay.”

Throat tight, he swallowed hard and reached for the tie beneath her belly button. Dave tugged at it until the belt gave way, and the halves of her robe split open like a curtain, revealing to him what he could have only imagined just seconds before. A bare line of flesh, from collar bone to pubic bone. The curve of her breasts. The soft swell of her belly. Another tug and the robe became a forgotten heap of cotton on the floor at their feet.

He paused. Allowed his thumb to find a home in the space between the vertebrae in her tailbone. The coccyx – a small, curved bone at the base of the spine – was extremely difficult to break, but he’d done it before. He'd made it look like a slip-and-fall accident. He could do it again if he wanted to, but he didn’t want to.

“I don’t want to hurt you,” he whispered as he guided his hands up her sides. He cupped her breasts and squeezed gently. “I won’t hurt you.”

"I know," she replied, tone strong and certain, bowing into his touch. "I know you won't, Dave."

He closed his eyes, pressed his nose to the crown of her head, and nudged at her ankle with his foot. He hadn’t said a word, but still, she’d listened beautifully and shifted her stance. That action alone was enough to get him buzzed, to fill his cock, and make his mouth water. When he opened his eyes, the sight of her ass stuck out and her hands braced on the counter made him groan.  

Dave unbuttoned and unzipped. Shoved his jeans and underwear past his hips. He knew he no longer deserved this, but he wanted it. He wanted her. Was starved for her. His body practically vibrated with a need so strong that it felt as if he could be broken all over again by it. His mind was so wild with anticipation, with such an overabundance of eagerness, that he nearly froze. 

“This morning,” she exhaled shakily, voice now tinged with shyness. “I touched – but I couldn’t. I��tried. I’ve been trying…”

The immobility that had threatened to overtake him fluttered away and was replaced by something akin to empathy. Teeth dug into his lower lip, Dave carefully reached between her thighs and found the evidence of what she’d barely managed to admit to. Hot. Wet. Swollen with arousal. He slowly spread his fingers around until they were coated in her slick, and she whimpered when he slid two deep inside her warmth.

She pushed back against him eagerly, and Dave may have been rusty and nervous as hell, but he hadn’t forgotten. The addition of another finger and slow, firm strokes to her clit with the pad of his thumb – that's what made her flutter and roll her hips. He pushed her hard toward her orgasm, not because he wanted to rush, or because he wanted his turn, but because he could sense just how badly she needed it. She needed it desperately – almost as desperately as he did. 

“How long?” Dave demanded gruffly. “How long have you been like this?”

She held the countertop in a white-knuckled grip, “Since the restaurant.”

It happened fast for her, just as he'd hoped. Her thighs twitched, and then, her knees wobbled. Pressed up against her as he was, Dave felt the way it trembled through her, the way her chest vibrated as she vocalized sounds of relief. He saw her through it, let his touch absorb the delicious aftershocks, and when he slowly slid his fingers out from between her legs, she whined in protest. 

“Still want it?” he asked against the shell of her ear.  

“I want it, Dave,” she exhaled with a nod. “I want you.”

Fingertips dug into the meat of her hips, Dave guided himself into her, right down to the base. He clocked her gasp. The way she strained on tiptoe. How her plush ass flexed against his groin. She adjusted, surrendered, and squeezed down hard around him like she’d be content to hold him within her, just like he was, for however long he desired.

Jaw clenched, eyes fixed on where they were joined, Dave eased back and pushed forward again. He watched, transfixed, as he disappeared inside of her. She was drenched, and his cock glistened with every retreat and thrust.

Paces matched, rhythm found, gratification coaxed until it burned painfully hot and bright. Hips sharply angled. Fast and deep. She whisper-chanted his name as he strummed her clit, and the scent of her shampoo, the soft backs of her thighs, her hands splayed wide across the countertop – so erotic, so beautiful…

“Feels good,” she murmured, words soft and blissed out. She pushed back down on him and stuttered out a breathless curse. “You feel so fucking good, Dave.”

Head drooped, the line from the nape of her neck to the slope of her shoulder was fully exposed. Compelled, without consideration or reason, suddenly greedy and inexplicably possessive, Dave sank his teeth into her flesh. An untamed sound escaped her throat, one that instantly became imprinted on his brain, and when she gushed around his cock, his head spun.   

He stroked her already oversensitive bundle of nerves until she jolted and whimpered and knocked what would’ve been his mug of coffee into the sink. Dave could feel the way her body warred, how eager she was to both drown in and escape from the onslaught. Her head lolled back against his shoulder, and with her face upturned and her eyes on him, he felt truly seen. 

And completely safe.    

“You want it inside,” Dave stated, words tumbling out before he could stop them. “Don’t you?”

She croaked out an unashamed, “Yes, I want it inside,” and that spurred him into doing perhaps two unwise, but wholly necessary things. Dave came inside her – rocked his hips and ground himself deep as his release rushed through him. Then, he kissed her – used his tongue to pry her mouth wide open and plunder. And she reciprocated, all muffled mewls as she held him within her, thighs pressed tight, and walls furiously clamped.

He grazed his teeth over the shell of her ear. Ghosted his mouth along the hinge of her jaw. Felt a pang of displeasure when he eventually slipped from her – an emotion that was almost immediately replaced by something dark and ferocious as he watched his come trickle down her inner thighs.

She turned slowly toward him and smiled, “Wanna go get tacos?”

Dave’s stomach growled and served as an answer. When she smiled, he decided she was more than worth the trouble.

And he wasn’t going anywhere.

[proxysql]

In today’s digital era, database performance is critical to the overall speed, stability, and scalability of modern applications. Whether you're running a transactional system, an analytics platform, or a hybrid database structure, maintaining optimal performance is essential to ensure seamless user experiences and operational efficiency.

In this blog, we'll explore effective strategies to improve database performance, reduce latency, and support growing data workloads without compromising system reliability.

1. Optimize Queries and Use Prepared Statements

Poorly written SQL queries are often the root cause of performance issues. Long-running or unoptimized queries can hog resources and slow down the entire system. Developers should focus on:

Using EXPLAIN plans to analyze query execution paths

Avoiding unnecessary columns or joins

Reducing the use of SELECT *

Applying appropriate filters and limits

Prepared statements can also boost performance by reducing parsing overhead and improving execution times for repeated queries.

2. Leverage Indexing Strategically

Indexes are powerful tools for speeding up data retrieval, but improper use can lead to overhead during insert and update operations. Indexes should be:

Applied selectively to frequently queried columns

Monitored for usage and dropped if rarely used

Regularly maintained to avoid fragmentation

Composite indexes can also be useful when multiple columns are queried together.

3. Implement Query Caching

Query caching can drastically reduce response times for frequent reads. By storing the results of expensive queries temporarily, you avoid reprocessing the same query multiple times. However, it's important to:

Set appropriate cache lifetimes

Avoid caching volatile or frequently changing data

Clear or invalidate cache when updates occur

Database proxy tools can help with intelligent query caching at the SQL layer.

4. Use Connection Pooling

Establishing database connections repeatedly consumes both time and resources. Connection pooling allows applications to reuse existing database connections, improving:

Response times

Resource management

Scalability under load

Connection pools can be fine-tuned based on application traffic patterns to ensure optimal throughput.

5. Partition Large Tables

Large tables with millions of records can suffer from slow read and write performance. Partitioning breaks these tables into smaller, manageable segments based on criteria like range, hash, or list. This helps:

Speed up query performance

Reduce index sizes

Improve maintenance tasks such as vacuuming or archiving

Partitioning also simplifies data retention policies and backup processes.

6. Monitor Performance Metrics Continuously

Database monitoring tools are essential to track performance metrics in real time. Key indicators to watch include:

Query execution time

Disk I/O and memory usage

Cache hit ratios

Lock contention and deadlocks

Proactive monitoring helps identify bottlenecks early and prevents system failures before they escalate.

7. Ensure Hardware and Infrastructure Support

While software optimization is key, underlying infrastructure also plays a significant role. Ensure your hardware supports current workloads by:

Using SSDs for faster data access

Scaling vertically (more RAM/CPU) or horizontally (sharding) as needed

Optimizing network latency for remote database connections

Cloud-native databases and managed services also offer built-in scaling options for dynamic workloads.

8. Regularly Update and Tune the Database Engine

Database engines release frequent updates to fix bugs, enhance performance, and introduce new features. Keeping your database engine up-to-date ensures:

Better performance tuning options

Improved security

Compatibility with modern application architectures

Additionally, fine-tuning engine parameters like buffer sizes, parallel execution, and timeout settings can significantly enhance throughput.

[quantuminnovationit]

How Can I Use Programmatic SEO to Launch a Niche Content Site?

Launching a niche content site can be both exciting and rewarding—especially when it's done with a smart strategy like programmatic SEO. Whether you're targeting a hyper-specific audience or aiming to dominate long-tail keywords, programmatic SEO can give you an edge by scaling your content without sacrificing quality. If you're looking to build a site that ranks fast and drives passive traffic, this is a strategy worth exploring. And if you're unsure where to start, a professional SEO agency Markham can help bring your vision to life.

What Is Programmatic SEO?

Programmatic SEO involves using automated tools and data to create large volumes of optimized pages—typically targeting long-tail keyword variations. Instead of manually writing each piece of content, programmatic SEO leverages templates, databases, and keyword patterns to scale content creation efficiently.

For example, a niche site about hiking trails might use programmatic SEO to create individual pages for every trail in Canada, each optimized for keywords like “best trail in [location]” or “hiking tips for [terrain].”

Steps to Launch a Niche Site Using Programmatic SEO

1. Identify Your Niche and Content Angle

Choose a niche that:

Has clear search demand

Allows for structured data (e.g., locations, products, how-to guides)

Has low to medium competition

Examples: electric bike comparisons, gluten-free restaurants by city, AI tools for writers.

2. Build a Keyword Dataset

Use SEO tools (like Ahrefs, Semrush, or Google Keyword Planner) to extract long-tail keyword variations. Focus on "X in Y" or "best [type] for [audience]" formats. If you're working with an SEO agency Markham, they can help with in-depth keyword clustering and search intent mapping.

3. Create Content Templates

Build templates that can dynamically populate content with variables like location, product type, or use case. A content template typically includes:

Intro paragraph

Keyword-rich headers

Dynamic tables or comparisons

FAQs

Internal links to related pages

4. Source and Structure Your Data

Use public datasets, APIs, or custom scraping to populate your content. Clean, accurate data is the backbone of programmatic SEO.

5. Automate Page Generation

Use platforms like Webflow (with CMS collections), WordPress (with custom post types), or even a headless CMS like Strapi to automate publishing. If you’re unsure about implementation, a skilled SEO agency Markham can develop a custom solution that integrates data, content, and SEO seamlessly.

6. Optimize for On-Page SEO

Every programmatically created page should include:

Title tags and meta descriptions with dynamic variables

Clean URL structures (e.g., /tools-for-freelancers/)

Internal linking between related pages

Schema markup (FAQ, Review, Product)

7. Track, Test, and Improve

Once live, monitor your pages via Google Search Console. Use A/B testing to refine titles, layouts, and content. Focus on improving pages with impressions but low click-through rates (CTR).

Why Work with an SEO Agency Markham?

Executing programmatic SEO at scale requires a mix of SEO strategy, web development, content structuring, and data management. A professional SEO agency Markham brings all these capabilities together, helping you:

Build a robust keyword strategy

Design efficient, scalable page templates

Ensure proper indexing and crawlability

Avoid duplication and thin content penalties

With local expertise and technical know-how, they help you launch faster, rank better, and grow sustainably.

Final Thoughts

Programmatic SEO is a powerful method to launch and scale a niche content site—if you do it right. By combining automation with strategic keyword targeting, you can dominate long-tail search and generate massive organic traffic. To streamline the process and avoid costly mistakes, partner with an experienced SEO agency Markham that understands both the technical and content sides of SEO.

Ready to build your niche empire? Programmatic SEO could be your best-kept secret to success

[secretindicator]

easy forex scalping strategy

Easy Forex Scalping Strategy: A Beginner-Friendly Guide

Table of Contents

https://secretindicator.com/product/forex-gold-m5-non-repaint-mt4-indicator/

Introduction to Forex Scalping

Why Choose Scalping?

Understanding the Basics

Key Indicators for Scalping

The Easy Forex Scalping Strategy

Step-by-Step Trading Setup

Risk Management

Best Pairs for Scalping

Trading Psychology and Discipline

Pros and Cons of Scalping

Tips for Scalping Success

Common Mistakes to Avoid

Tools and Platforms for Scalping

Case Study Example

Conclusion

1. Introduction to Forex Scalping

Forex scalping is a trading method that focuses on profiting from small price changes. It involves entering and exiting trades in a matter of seconds or minutes, aiming for quick profits multiple times a day.

Scalping isn't about catching big moves—it's about consistency and repetition. The goal is to accumulate small gains that add up to significant profits over time.

2. Why Choose Scalping?

Scalping attracts many traders for several reasons:

Quick Results: No need to wait days or weeks for trade outcomes.

Less Exposure: Short market exposure reduces risk from unexpected news.

Frequent Opportunities: Scalpers can find dozens of opportunities daily.

High Win Rate Potential: With the right setup, a trader can win a majority of trades.

However, it also requires focus, speed, and discipline.

3. Understanding the Basics

What is Scalping?

Scalping involves:

Very short trade durations: A few seconds to a few minutes.

High trade volume: Many trades per day.

Low profit per trade: Often 5 to 15 pips.

High leverage (used cautiously): Enhances small gains.

Timeframes

Scalping is typically done on:

1-minute (M1) and 5-minute (M5) charts.

4. Key Indicators for Scalping

While scalping strategies can vary, the following indicators are widely used and effective:

1. Exponential Moving Averages (EMA)

9 EMA and 21 EMA: Great for identifying short-term trends and crossovers.

2. Stochastic Oscillator

Shows overbought and oversold conditions, useful for pinpointing reversals.

3. Relative Strength Index (RSI)

Measures momentum and helps confirm trade entries and exits.

4. Volume

Confirms the strength of a move.

5. The Easy Forex Scalping Strategy

This strategy uses the following tools:

Timeframe: 1-Minute Chart (M1)

Indicators:

9 EMA (fast)

21 EMA (slow)

RSI (14) with a 70/30 level

Stochastic Oscillator (5,3,3)

Currency Pairs: EUR/USD, GBP/USD, USD/JPY (high liquidity and low spreads)

Strategy Concept

Trade in the direction of the trend.

Enter on pullbacks confirmed by stochastic and RSI.

Exit quickly with a small target.

6. Step-by-Step Trading Setup

Step 1: Identify the Trend

Use the 9 EMA and 21 EMA:

Bullish Trend: 9 EMA is above 21 EMA.

Bearish Trend: 9 EMA is below 21 EMA.

Step 2: Wait for a Pullback

Wait for price to pull back near the EMAs.

Step 3: Confirm With RSI

Buy Setup: RSI between 30-50 and turning up.

Sell Setup: RSI between 50-70 and turning down.

Step 4: Confirm With Stochastic

For buys: Stochastic crosses upward from below 20.

For sells: Stochastic crosses downward from above 80.

Step 5: Entry

Enter the trade when both RSI and Stochastic confirm.

Set a tight stop-loss (5–7 pips).

Step 6: Exit

Take profit at 10–15 pips.

Exit early if indicators reverse or if price moves too slowly.

7. Risk Management

Scalping success depends largely on risk management:

Risk per trade: Max 1% of your account balance.

Stop-loss: Always use one, even if it's tight.

Leverage: Use low leverage to protect capital.

Example: If you have a $1,000 account and risk 1% per trade, that’s $10 per trade. With a 5-pip stop loss, trade 0.2 lots (20,000 units) on EUR/USD.

8. Best Pairs for Scalping

Choose pairs with:

Tight spreads (below 1 pip)

High liquidity

Top pairs:

EUR/USD

GBP/USD

USD/JPY

AUD/USD

EUR/JPY

9. Trading Psychology and Discipline

Scalping can be mentally taxing. Key psychological principles:

Stay focused — distractions can cost money.

Stick to the plan — don’t chase losses.

Accept losses — they are part of the game.

Take breaks — trading fatigue leads to mistakes.

10. Pros and Cons of Scalping

Pros

Quick profits

Many opportunities

Less overnight risk

Works well in all markets

Cons

Requires intense focus

Can be emotionally draining

High transaction costs

Not ideal for everyone

11. Tips for Scalping Success

Use ECN brokers for faster execution.

Avoid scalping during news releases.

Use hotkeys or one-click trading tools.

Practice on demo first.

Keep a trading journal for improvement.

12. Common Mistakes to Avoid

Overtrading: Quality > quantity.

Ignoring the spread: Small trades mean spread matters a lot.

No stop-loss: Recipe for disaster.

Chasing the market: Leads to poor entries.

13. Tools and Platforms for Scalping

Recommended Platforms:

MetaTrader 4/5

cTrader

NinjaTrader

TradingView (for analysis)

Essential Tools:

Economic calendar (e.g., Forex Factory)

Fast internet connection

VPS for automated scalping

14. Case Study Example

Let’s walk through a live trade example on EUR/USD 1-minute chart.

Conditions:

Trend: 9 EMA is above 21 EMA — uptrend.

Price pulls back near 21 EMA.

RSI is at 40 and turning upward.

Stochastic crosses upward at 18.

Action:

Entry: Buy at 1.0865

Stop-loss: 1.0860 (5 pips)

Take profit: 1.0875 (10 pips)

Result: TP hit in 3 minutes.

15. Conclusion

Scalping, when done correctly, is a powerful and consistent way to trade Forex. The easy scalping strategy outlined in this guide uses simple indicators, clear entry/exit rules, and solid risk management principles. It’s ideal for beginners who want a structured approach.

Key Takeaways:

Trade in the direction of the short-term trend.

Use EMAs, RSI, and Stochastic for confirmations.

Aim for small, consistent wins.

Use tight stop-loss and sound risk management.

Stay disciplined and avoid emotional decisions.

If you master this strategy, keep refining it with backtesting and experience. With time, you can scale up, trade more confidently, and reach consistent profitability.

[xpressluna]

This SQL Trick Cut My Query Time by 80%

How One Simple Change Supercharged My Database Performance

If you work with SQL, you’ve probably spent hours trying to optimize slow-running queries — tweaking joins, rewriting subqueries, or even questioning your career choices. I’ve been there. But recently, I discovered a deceptively simple trick that cut my query time by 80%, and I wish I had known it sooner.

Here’s the full breakdown of the trick, how it works, and how you can apply it right now.

🧠 The Problem: Slow Query in a Large Dataset

I was working with a PostgreSQL database containing millions of records. The goal was to generate monthly reports from a transactions table joined with users and products. My query took over 35 seconds to return, and performance got worse as the data grew.

Here’s a simplified version of the original query:

sql

SELECT

u.user_id,

SUM(t.amount) AS total_spent

FROM

transactions t

JOIN

users u ON t.user_id = u.user_id

WHERE

t.created_at >= '2024-01-01'

AND t.created_at < '2024-02-01'

GROUP BY

u.user_id, http://u.name;

No complex logic. But still painfully slow.

⚡ The Trick: Use a CTE to Pre-Filter Before the Join

The major inefficiency here? The join was happening before the filtering. Even though we were only interested in one month’s data, the database had to scan and join millions of rows first — then apply the WHERE clause.

✅ Solution: Filter early using a CTE (Common Table Expression)

Here’s the optimized version:

sql

WITH filtered_transactions AS (

SELECT *

FROM transactions

WHERE created_at >= '2024-01-01'

AND created_at < '2024-02-01'

)

SELECT

u.user_id,

SUM(t.amount) AS total_spent

FROM

filtered_transactions t

JOIN

users u ON t.user_id = u.user_id

GROUP BY

u.user_id, http://u.name;

Result: Query time dropped from 35 seconds to just 7 seconds.

That’s an 80% improvement — with no hardware changes or indexing.

🧩 Why This Works

Databases (especially PostgreSQL and MySQL) optimize join order internally, but sometimes they fail to push filters deep into the query plan.

By isolating the filtered dataset before the join, you:

Reduce the number of rows being joined

Shrink the working memory needed for the query

Speed up sorting, grouping, and aggregation

This technique is especially effective when:

You’re working with time-series data

Joins involve large or denormalized tables

Filters eliminate a large portion of rows

🔍 Bonus Optimization: Add Indexes on Filtered Columns

To make this trick even more effective, add an index on created_at in the transactions table:

sql

CREATE INDEX idx_transactions_created_at ON transactions(created_at);

This allows the database to quickly locate rows for the date range, making the CTE filter lightning-fast.

🛠 When Not to Use This

While this trick is powerful, it’s not always ideal. Avoid it when:

Your filter is trivial (e.g., matches 99% of rows)

The CTE becomes more complex than the base query

Your database’s planner is already optimizing joins well (check the EXPLAIN plan)

🧾 Final Takeaway

You don’t need exotic query tuning or complex indexing strategies to speed up SQL performance. Sometimes, just changing the order of operations — like filtering before joining — is enough to make your query fly.

“Think like the database. The less work you give it, the faster it moves.”

If your SQL queries are running slow, try this CTE filtering trick before diving into advanced optimization. It might just save your day — or your job.

Would you like this as a Medium post, technical blog entry, or email tutorial series?

[govindhtech]

Column Granularity Indexing in BigQuery Alters Query Speed

Indices by Column Granularity

BigQuery Improves Search Query Efficiency and Cost with Column-Granularity Indexing

The public preview of Google Cloud BigQuery's column granularity indexing improves its indexing capabilities. With this new functionality, query performance and cost effectiveness should improve significantly.

BigQuery organises table data into physical files and stores data columnarly, with each column having its own file block. The file-level default search index maps data tokens to files. This strategy effectively narrows the search field by selectively scanning relevant files, especially when search tokens are rare and only appear in a few files.

However, when search tokens are ubiquitous across columns but selective inside others, they appear in most files and reduce the file-level index's utility. Consider a table with Title and Content columns for “Google Cloud Logging” articles. Even if the combination or inclusion in the Title column is rare, “google,” “cloud,” and “logging” may be in every file. The tokens exist in every file, thus a Title column query would still require scanning every file even with the default file-level index on both columns.

col-level index

In this case, column-granular indexing is essential. This new feature improves indexes by adding column-specific data. This lets BigQuery find relevant data in columns even when search tokens are used often across the table's files.

As seen in TechArticles, a search index with column granularity determined by OPTIONS (default_index_column_granularity = ‘COLUMN’) keeps token column information. BigQuery may use index column information to search for “Google Cloud Logging” in the Title column. It can recognise files in the ‘Title’ column with ‘google’, ‘cloud’, and ‘logging’ tokens. Since only ‘file1’ includes all three tokens in the ‘Title’ column, BigQuery can scan one file instead of all four.

This capacity provides two important benefits immediately:

Accurately locating relevant data in columns speeds up query execution, especially for queries using selective search tokens.

Better index pruning reduces processed bytes and slot time, lowering expenses instantly.

These benefits are especially useful when searches filter or aggregate data by column or when search tokens are common but selective within columns. Even though the default index reduced search space, column granularity indexing improved execution time, processed bytes, and slot consumption on a 1TB table containing logging data.

BigQuery column-granular indexing

Column-granular indexing improves query performance and cost. Recommended for users:

Examine query patterns to find high-impact columns for optimum results.

Monitor performance and adjust indexing plan as needed.

Indexing and storage costs may climb.

Users can use this feature by enabling column-granular indexing. A CREATE SEARCH INDEX DDL document offers further information. This new functionality improves BigQuery search queries, especially for large datasets and complex data structures where precise column information has to be promptly obtained.

[greatonlinetrainingsposts]

Advanced SAS Programming Techniques: Tips to Optimize Your Code and Workflow

In today’s data-driven world, SAS programming continues to play a critical role in analytics, data management, and business intelligence. While many professionals become comfortable with basic data handling and procedures, the true value of SAS lies in mastering advanced techniques that enhance both performance and efficiency.

If you're a data analyst, statistician, or programmer looking to level up your SAS programming skills, this guide will walk you through key tips and strategies to write better, faster, and cleaner code.

1. Why Advanced SAS Programming Matters

Basic SAS skills will help you clean, process, and analyze data. But advanced SAS programming is where productivity, scalability, and automation begin to shine. In fast-paced environments like clinical trials, finance, or e-commerce analytics, optimized SAS code can save hours of manual effort and significantly reduce errors.

Moreover, as datasets grow in size and complexity, writing efficient and scalable code becomes essential to avoid memory issues and long run times.

2. Use Macros to Automate and Reuse Code

One of the most powerful features in SAS is its macro language. Macros allow you to automate repetitive tasks, simplify your programs, and make your code easier to maintain.

By using macro variables and macro programs, you can dynamically generate code based on different input parameters. This not only saves time but also reduces the risk of manual coding errors.

For example, if you're running the same analysis for different regions or time periods, you can use a macro to loop through those values instead of writing separate blocks of code.

3. Efficient Data Step Programming

The DATA step is the backbone of most SAS programming workflows. To write efficient DATA steps, consider the following best practices:

Keep only the variables you need using the KEEP or DROP statements.

Read only necessary observations using conditional logic.

Use IF-THEN/ELSE efficiently to reduce the number of comparisons.

Minimize sorting operations by organizing your data early.

Every unnecessary line of code adds processing time, especially when you're working with millions of rows. Clean, purposeful DATA steps lead to faster execution and easier debugging.

4. Leverage PROC SQL for Flexible Data Manipulation

While the DATA step is excellent for row-by-row operations, PROC SQL is your best friend for more complex joins and aggregations. It allows you to:

Join multiple datasets without pre-sorting.

Perform subqueries and advanced filtering.

Aggregate data in a concise way.

Integrating PROC SQL into your workflow not only increases flexibility but also helps when transitioning between SAS and other SQL-based platforms.

5. Profiling and Debugging with the Log

Many programmers overlook the power of the SAS Log. This tool gives detailed information about data step processing, including the number of observations read, written, and the amount of time taken.

Learning how to read and interpret the log efficiently helps in identifying bottlenecks and bugs. Use options like OPTIONS MPRINT, MLOGIC, and SYMBOLGEN for debugging macro code and trace the flow of your program.

6. Indexing and Hash Objects

When working with large datasets, performance can be greatly improved using indexing and hash tables.

Indexing helps SAS find and retrieve data faster during BY or WHERE operations.

Hash objects are in-memory lookup tables that offer high-speed matching and merging without sorting, ideal for real-time data operations.

These features are more advanced but worth learning for performance-heavy tasks.

7. Modular Programming for Maintainability

Breaking your code into modular, reusable components is a best practice in any language, and SAS is no exception. Use INCLUDE files or macros to structure your programs logically.

This makes the code easier to understand and enables team collaboration. When multiple people are working on the same project, a well-organized codebase saves time and reduces errors.

8. Documenting Your Code

Good programmers write code that others can understand. Great programmers write code that they themselves can understand a year later. Use comments to explain:

Why certain logic is used

How parameters are defined

The purpose of a macro or subroutine

It’s not about writing more—it’s about writing smarter.

9. Continuous Learning and Community Engagement

The SAS community is active and supportive. Explore the SAS blogs, attend webinars, and participate in SAS user groups. Keeping up with updates, new procedures, and best practices ensures your SAS programming skills stay relevant.

[neiljordansimon]

How We Improved Site Speed for a Client's PHP Website

When a client approached us with concerns about their website's loading speed and inconsistent performance, we recognized this as a challenge common among businesses with legacy PHP applications. Site speed plays a critical role in user experience, SEO rankings, and overall digital success. Slow performance can directly impact bounce rates and conversions, which is why PHP development companies must prioritize speed optimization in every project.

In this case study, we’ll walk through the methods we used to optimize a PHP-based website for better speed and performance.

Initial Assessment and Problem Identification

The first step was a full performance audit. Using tools like Google PageSpeed Insights, GTmetrix, and server logs, we uncovered several key issues:

Inefficient database queries

No caching mechanisms in place

Poorly optimized assets (JavaScript, CSS, and images)

High server response times

These issues are not uncommon for websites built a few years ago without ongoing optimization. Many PHP development companies in USA encounter such challenges, especially when websites evolve without scalable backend solutions.

Key Optimization Techniques We Applied

1. Optimizing Database Performance

The website’s dynamic content relied on complex and sometimes redundant SQL queries. We restructured these queries and added indexing where necessary. By reducing query execution time, we achieved noticeable backend performance gains.

2. Implementing Caching

To reduce load on the server and improve response time for repeat visitors, we enabled:

Opcode caching with OPcache

Object caching using Redis

Full-page caching for static and semi-dynamic content

Caching is one of the most effective ways for top PHP development companies in USA to immediately enhance site speed with minimal risk to core functionality.

3. Asset Optimization

We minified all CSS and JavaScript files, removed unused styles, and bundled them efficiently to reduce HTTP requests. Additionally, we enabled Gzip compression and browser caching via .htaccess to improve frontend performance.

4. Image and Media Optimization

Large image files were replaced with compressed versions in modern formats like WebP. We also implemented lazy loading to defer offscreen images from loading until they were needed.

5. Server Configuration Enhancements

Our team fine-tuned PHP-FPM and Apache configurations to ensure that the server handled traffic more efficiently. We increased memory limits, adjusted timeout settings, and introduced monitoring tools to keep track of resource usage.

Results Achieved

After deploying these improvements, the client experienced:

70% faster page load times

A 40% drop in bounce rate

Improved search engine visibility

A smoother and more responsive admin dashboard

These outcomes are a testament to what experienced PHP development companies can accomplish with the right blend of strategy, tools, and technical expertise.

Long-Term Strategy

Speed optimization isn’t a one-time fix. We helped the client set up automated performance reports and regular maintenance routines. This proactive approach ensures their website remains fast even as traffic increases or new features are introduced.

Final Thoughts

For businesses running PHP-based websites, performance optimization should be an ongoing priority. Whether you're maintaining a legacy application or building something new, partnering with professionals matters.

Our success in this project reflects the value that top PHP development companies in USA bring to the table. With hands-on experience, performance tuning capabilities, and scalable development practices, we help our clients stay competitive in the digital space.

If you're looking to enhance your website's performance, collaborating with trusted PHP development companies in USA can lead to transformative results.

[proxysql]

How to Improve Database Performance with Smart Optimization Techniques

Database performance is critical to the efficiency and responsiveness of any data-driven application. As data volumes grow and user expectations rise, ensuring your database runs smoothly becomes a top priority. Whether you're managing an e-commerce platform, financial software, or enterprise systems, sluggish database queries can drastically hinder user experience and business productivity.

In this guide, we’ll explore practical and high-impact strategies to improve database performance, reduce latency, and increase throughput.

1. Optimize Your Queries

Poorly written queries are one of the most common causes of database performance issues. Avoid using SELECT * when you only need specific columns. Analyze query execution plans to understand how data is being retrieved and identify potential inefficiencies.

Use indexed columns in WHERE, JOIN, and ORDER BY clauses to take full advantage of the database indexing system.

2. Index Strategically

Indexes are essential for speeding up data retrieval, but too many indexes can hurt write performance and consume excessive storage. Prioritize indexing on columns used in search conditions and join operations. Regularly review and remove unused or redundant indexes.

3. Implement Connection Pooling

Connection pooling allows multiple application users to share a limited number of database connections. This reduces the overhead of opening and closing connections repeatedly, which can significantly improve performance, especially under heavy load.

4. Cache Frequently Accessed Data

Use caching layers to avoid unnecessary hits to the database. Frequently accessed and rarely changing data—such as configuration settings or product catalogs—can be stored in in-memory caches like Redis or Memcached. This reduces read latency and database load.

5. Partition Large Tables

Partitioning splits a large table into smaller, more manageable pieces without altering the logical structure. This improves performance for queries that target only a subset of the data. Choose partitioning strategies based on date, region, or other logical divisions relevant to your dataset.

6. Monitor and Tune Regularly

Database performance isn’t a one-time fix—it requires continuous monitoring and tuning. Use performance monitoring tools to track query execution times, slow queries, buffer usage, and I/O patterns. Adjust configurations and SQL statements accordingly to align with evolving workloads.

7. Offload Reads with Replication

Use read replicas to distribute query load, especially for read-heavy applications. Replication allows you to spread read operations across multiple servers, freeing up the primary database to focus on write operations and reducing overall latency.

8. Control Concurrency and Locking

Poor concurrency control can lead to lock contention and delays. Ensure your transactions are short and efficient. Use appropriate isolation levels to avoid unnecessary locking, and understand the impact of each level on performance and data integrity.

[souhaillaghchimdev]

Advanced Database Design

As applications grow in size and complexity, the design of their underlying databases becomes critical for performance, scalability, and maintainability. Advanced database design goes beyond basic tables and relationships—it involves deep understanding of normalization, indexing, data modeling, and optimization strategies.

1. Data Modeling Techniques

Advanced design starts with a well-thought-out data model. Common modeling approaches include:

Entity-Relationship (ER) Model: Useful for designing relational databases.

Object-Oriented Model: Ideal when working with object-relational databases.

Star and Snowflake Schemas: Used in data warehouses for efficient querying.

2. Normalization and Denormalization

Normalization: The process of organizing data to reduce redundancy and improve integrity (up to 3NF or BCNF).

Denormalization: In some cases, duplicating data improves read performance in analytical systems.

3. Indexing Strategies

Indexes are essential for query performance. Common types include:

B-Tree Index: Standard index type in most databases.

Hash Index: Good for equality comparisons.

Composite Index: Combines multiple columns for multi-column searches.

Full-Text Index: Optimized for text search operations.

4. Partitioning and Sharding

Partitioning: Splits a large table into smaller, manageable pieces (horizontal or vertical).

Sharding: Distributes database across multiple machines for scalability.

5. Advanced SQL Techniques

Common Table Expressions (CTEs): Temporary result sets for organizing complex queries.

Window Functions: Perform calculations across a set of table rows related to the current row.

Stored Procedures & Triggers: Automate tasks and enforce business logic at the database level.

6. Data Integrity and Constraints

Primary and Foreign Keys: Enforce relational integrity.

CHECK Constraints: Validate data against specific rules.

Unique Constraints: Ensure column values are not duplicated.

7. Security and Access Control

Security is crucial in database design. Best practices include:

Implementing role-based access control (RBAC).

Encrypting sensitive data both at rest and in transit.

Using parameterized queries to prevent SQL injection.

8. Backup and Recovery Planning

Design your database with disaster recovery in mind:

Automate daily backups.

Test recovery procedures regularly.

Use replication for high availability.

9. Monitoring and Optimization

Tools like pgAdmin (PostgreSQL), MySQL Workbench, and MongoDB Compass help in identifying bottlenecks and optimizing performance.

10. Choosing the Right Database System

Relational: MySQL, PostgreSQL, Oracle (ideal for structured data and ACID compliance).

NoSQL: MongoDB, Cassandra, CouchDB (great for scalability and unstructured data).

NewSQL: CockroachDB, Google Spanner (combines NoSQL scalability with relational features).

Conclusion

Advanced database design is a balancing act between normalization, performance, and scalability. By applying best practices and modern tools, developers can ensure that their systems are robust, efficient, and ready to handle growing data demands. Whether you’re designing a high-traffic e-commerce app or a complex analytics engine, investing time in proper database architecture pays off in the long run.

[udayadaequarelistany]

Why Is My eCommerce Site Slow Even with Good Hosting?

Introduction

You’re paying for high-performance hosting, but your eCommerce site still loads slowly. Pages lag, product images crawl in, and your bounce rate is skyrocketing. Sound familiar?

Good hosting is only part of the performance puzzle. In this blog, we’ll explore why your eCommerce website development efforts might still result in a slow site — and exactly what you can do to fix it.

Common Reasons Your eCommerce Site Is Still Slow 1. Unoptimized Images Large image files are one of the top culprits of slow load times. Avoid uploading raw photos from DSLR or phone cameras. Use tools like TinyPNG or WebP formats to compress images without losing quality.

Tip: Use lazy loading for product images and carousels.

2. Too Many Third-Party Scripts Live chats, trackers, heatmaps, and plugins often add JavaScript bloat. Scripts from Facebook Pixel, Google Tag Manager, and review widgets can block rendering.

Tip: Load non-critical scripts asynchronously or defer them.

3. Heavy Themes or Builders Are you using a feature-heavy theme or drag-and-drop builder? Themes built for flexibility can be bloated. Shopify and WooCommerce themes with unnecessary animations or sliders slow everything down.

Tip: Use lightweight, performance-optimized themes (like Dawn for Shopify or Astra for WooCommerce).

4. Inefficient Code or Customizations Custom code by freelancers or agencies might not be optimized. Loops, queries, or AJAX calls in product pages could slow down your site.

Tip: Audit your codebase regularly or use tools like GTmetrix and PageSpeed Insights to find bottlenecks.

5. Uncached Dynamic Content Even with good hosting, uncached pages can cause lags. Product pages, category filters, and carts are often dynamically generated.

Tip: Use page caching (e.g., Varnish, WP Rocket) and CDN edge caching (Cloudflare, BunnyCDN).

6. Large or Unoptimized Database Your store database grows with every product, order, and customer. Poor indexing or bloated tables cause slow queries. This is especially common in WooCommerce or Magento.

Tip: Optimize your database monthly using plugins like WP-Optimize or direct SQL commands.

7. Overloaded Frontend with Too Many Requests Each button, font, icon, and script is an HTTP request. Too many requests slow everything down.

Tip: Minify CSS and JS files, combine where possible, and reduce HTTP requests using tools like Autoptimize.

8. No Content Delivery Network (CDN) Even with fast hosting, visitors farther from your server face delays in loading your website.

Tip: Use a CDN like Cloudflare or BunnyCDN to serve assets closer to your users worldwide.

How to Diagnose the Real Problem Use these free tools to pinpoint the exact cause:

Google PageSpeed Insights — shows Core Web Vitals

GTmetrix — waterfall view of every request

Chrome DevTools — identify blocking assets

Pingdom — great for global speed tests

Hosting Alone Isn’t Enough Your hosting might be fast, but your site architecture, plugins, and content delivery strategy matter just as much.

Think of hosting as a highway. If your store is a traffic jam of scripts, bloated images, and detours, speed still suffers. That’s why many businesses turn to a best eCommerce website development company that can take performance optimization seriously from the ground up.

Conclusion If you’re wondering, “Why is my eCommerce site slow even with good hosting?”, the answer likely lies in:

Poor frontend performance

Unoptimized assets

Database or plugin bloat

Start with a full site audit. Optimize images, scripts, and theme. Use caching and a CDN.

Speed isn’t just about user experience — it’s an SEO and sales factor. A few strategic improvements can significantly reduce load times, improve conversions, and lower bounce rates. For scalable and reliable results, consider working with an experienced eCommerce solutions provider in India that understands performance, user behavior, and growth strategies.

[krishnaseoconsulting]

SEO Trends in Hamburg: What Businesses Need to Know This Year

In today’s fast-paced digital landscape, businesses in Hamburg must stay ahead of evolving SEO trends to remain competitive. Whether you run a small local shop or a large enterprise, search engine optimization (SEO) plays a crucial role in attracting customers and driving growth. As a leading SEO strategist in Hamburg, I’ve analyzed the latest trends shaping the industry this year. Here’s what businesses need to know to optimize their online presence effectively.

1. The Rise of AI-Driven SEO

Artificial Intelligence (AI) is transforming the way search engines rank content. Google's AI-driven updates, such as Google’s Search Generative Experience (SGE) and RankBrain, prioritize high-quality, user-focused content. To stay ahead, businesses should: ✔ Use natural language processing (NLP) in their content ✔ Focus on answering user queries clearly and concisely ✔ Optimize for featured snippets and voice search

2. Local SEO Remains Crucial for Hamburg Businesses

With more people searching for services “near me”, local SEO is more important than ever. To improve your local rankings in Hamburg: ✔ Optimize your Google Business Profile (GBP) with accurate details ✔ Encourage customer reviews and respond to them ✔ Use location-based keywords (e.g., SEO strategist Hamburg, best marketing agency Hamburg) ✔ Get listed in local directories like Yelp, TripAdvisor, and Hamburg Chamber of Commerce

3. Mobile-First SEO: A Must for Higher Rankings

Google’s mobile-first indexing means that your website’s mobile version determines its ranking. If your site isn’t mobile-friendly, you could lose potential customers. Ensure that you: ✔ Use a responsive website design ✔ Optimize page speed for mobile users ✔ Keep navigation simple and user-friendly

4. E-E-A-T: Google's Focus on Trustworthy Content

Google emphasizes Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) when ranking content. To align with this trend: ✔ Publish high-quality, expert-driven content ✔ Build backlinks from reputable sites ✔ Include author bios and credentials on content pages

5. Zero-Click Searches & Featured Snippets

More users get answers directly from Google’s featured snippets without clicking any links. To optimize for zero-click searches: ✔ Use structured data (schema markup) ✔ Format content in FAQ-style sections ✔ Include bullet points and tables for easy readability

6. Video SEO for Higher Engagement

With platforms like YouTube and TikTok growing rapidly, video SEO is essential. To improve rankings: ✔ Add relevant keywords to video titles and descriptions ✔ Create transcripts for accessibility ✔ Embed videos on your website to improve dwell time

7. Core Web Vitals: A Ranking Factor You Can’t Ignore

Google’s Core Web Vitals measure user experience based on: ✔ Largest Contentful Paint (LCP) – How fast a page loads ✔ First Input Delay (FID) – How quickly it becomes interactive ✔ Cumulative Layout Shift (CLS) – How stable the page layout is Improving these factors enhances user experience and search rankings.

8. Voice Search Optimization

With the rise of smart assistants like Siri and Google Assistant, more people are using voice search. To optimize for it: ✔ Use conversational keywords ✔ Optimize for question-based queries (e.g., Where can I find an SEO strategist in Hamburg?) ✔ Ensure fast page loading speed

Final Thoughts: Stay Ahead with an SEO Strategist in Hamburg

SEO is constantly evolving, and keeping up with these trends is vital for businesses in Hamburg. Whether you need keyword research, content optimization, or local SEO strategies, working with an SEO strategist can help you achieve sustainable growth.

Want to improve your website’s rankings and visibility? Contact Krishna Shekhar today for expert SEO strategies in Hamburg! 🚀

[allthebrazilianpolitics]

Tighter credit creates challenges and opportunities, Brazil's fund managers say

With interest rates at 14.25%, asset managers favor inflation-linked bonds and diversified credit over high-grade corporate debt

With the benchmark Selic rate at 14.25% per year and the possibility of further hikes, 2025 has proven to be a challenging year for Brazilian corporate credit assets. Still, there are opportunities, asset managers say. Inflation-linked, tax-exempt instruments are currently considered a better alternative than securities indexed to the CDI, the benchmark rate for interbank lending.

For Lígia Porchat, founding partner at Atena Capital, regardless of the scenario, it is essential to focus on price and evaluate credit as one would assess a stock. While the CDI works against investors, “real interest rates are practically free,” she said. In her view, funds can lock in a yield between 7.5% and 7.8% over a three-year horizon.

She warned that while CDI-linked portfolios, such as infrastructure funds, continue to attract large inflows, they won’t shield investors if credit spreads widen—unlike inflation-linked (IPCA) funds, which she said offer protection if everything goes wrong.

Pierre Jadoul, executive director in charge of credit strategies at ARX, agreed that this is not the best time to invest in CDI-linked securities or portfolios. “Anyone doing so will be leaving on the table the opportunity to lock in a high real interest rate,” he said, calling it possibly the best chance of the decade, particularly in long-term, tax-exempt securities.

Continue reading.

[dynamicscommunity101]

AX 2012 Interview Questions and Answers for Beginners and Experts

Microsoft Dynamics AX 2012 is a powerful ERP answer that facilitates organizations streamline their operations. Whether you're a newbie or an professional, making ready for an interview associated with AX 2012 requires a radical knowledge of its core standards, functionalities, and technical factors. Below is a list of commonly requested AX 2012 interview questions together with their solutions.

Basic AX 2012 Interview Questions

What is Microsoft Dynamics AX 2012?Microsoft Dynamics AX 2012 is an company aid planning (ERP) solution advanced with the aid of Microsoft. It is designed for large and mid-sized groups to manage finance, supply chain, manufacturing, and client relationship control.

What are the important thing features of AX 2012?

Role-primarily based user experience

Strong financial control skills

Advanced warehouse and deliver chain management

Workflow automation

Enhanced reporting with SSRS (SQL Server Reporting Services)

What is the distinction between AX 2009 and AX 2012?

AX 2012 introduced a new data version with the introduction of surrogate keys.

The MorphX IDE changed into replaced with the Visual Studio development environment.

Improved workflow and role-based totally get right of entry to manipulate.

What is the AOT (Application Object Tree) in AX 2012?The AOT is a hierarchical shape used to keep and manipulate objects like tables, bureaucracy, reports, lessons, and queries in AX 2012.

Explain the usage of the Data Dictionary in AX 2012.The Data Dictionary contains definitions of tables, information types, family members, and indexes utilized in AX 2012. It guarantees facts integrity and consistency across the device.

Technical AX 2012 Interview Questions

What are the distinctive sorts of tables in AX 2012?

Regular tables

Temporary tables

In Memory tables

System tables

What is the distinction between In Memory and TempDB tables?

In Memory tables shop information within the purchaser memory and aren't continual.

Temp DB tables save brief statistics in SQL Server and are session-unique.

What is X++ and the way is it utilized in AX 2012?X++ is an item-oriented programming language used in AX 2012 for growing business good judgment, creating custom modules, and automating processes.

What is the cause of the CIL (Common Intermediate Language) in AX 2012?CIL is used to convert X++ code into .NET IL, enhancing overall performance by using enabling execution at the .NET runtime degree.

How do you debug X++ code in AX 2012?Debugging may be accomplished the use of the X++ Debugger or with the aid of enabling the Just-In-Time Debugging function in Visual Studio.

Advanced AX 2012 Interview Questions

What is a Query Object in AX 2012?A Query Object is used to retrieve statistics from tables using joins, tiers, and sorting.

What are Services in AX 2012, and what sorts are to be had?

Document Services (for replacing statistics)

Custom Services (for exposing X++ logic as a carrier)

System Services (metadata, question, and user consultation offerings)

Explain the concept of Workflows in AX 2012.Workflows allow the automation of commercial enterprise techniques, together with approvals, via defining steps and assigning responsibilities to users.

What is the purpose of the SysOperation Framework in AX 2012?It is a substitute for RunBaseBatch framework, used for walking techniques asynchronously with higher scalability.

How do you optimize overall performance in AX 2012?

Using indexes effectively

Optimizing queries

Implementing caching strategies

Using batch processing for massive facts operations

Conclusion

By understanding those AX 2012 interview questions, applicants can successfully put together for interviews. Whether you're a novice or an experienced expert, gaining knowledge of those topics will boost your self assurance and help you secure a role in Microsoft Dynamics AX 2012 tasks.