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| import Label from '@/components/SimpleLabel' | ||
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| const Body = () => { | ||
| const listStyle = 'list-disc mx-6 mt-0 mb-5' | ||
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| return ( | ||
| <> | ||
| <p> | ||
| A write-back cache is a type of caching mechanism where data | ||
| modifications are initially written to the cache rather than directly to | ||
| the main database. This approach enhances performance by reducing the | ||
| number of direct write operations to the database, as the cached data is | ||
| written back to the database at a later time. Write-back caching is | ||
| particularly beneficial in high-write frequency applications and | ||
| scenarios requiring quick data access and lower latency. However, it | ||
| requires careful management to ensure data consistency and integrity, as | ||
| there is a risk of data loss if the cache fails before the data is | ||
| written to the database. | ||
| </p> | ||
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| <p className="mt-2"> | ||
| <span className="font-bold text-lg">When to Use Write-Back Cache:</span> | ||
| </p> | ||
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| <ul className={listStyle}> | ||
| <li> | ||
| <Label text="High Write Frequency" /> When the application has a high | ||
| volume of write operations, and performance is critical. The | ||
| write-back cache can reduce the number of write operations to the | ||
| database, thus improving performance. | ||
| </li> | ||
| <li> | ||
| <Label text="Batch Processing" /> In scenarios where data can be | ||
| processed in batches, such as analytics workloads where intermediate | ||
| results can be cached and written to the database later. | ||
| </li> | ||
| <li> | ||
| <Label text="Temporary Data Storage" /> When dealing with temporary | ||
| data that does not need immediate persistence, such as session data in | ||
| a web application. | ||
| </li> | ||
| <li> | ||
| <Label text="Network Latency" /> When the database is hosted on a | ||
| remote server, and reducing the number of network calls is beneficial. | ||
| </li> | ||
| <li> | ||
| <Label text="Cost Optimization" /> In cloud environments where | ||
| database writes incur cost, reducing the number of direct writes can | ||
| lead to cost savings. | ||
| </li> | ||
| </ul> | ||
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| <p className="mt-1"> | ||
| <span className="font-bold text-lg"> | ||
| When to Avoid Write-Back Cache: | ||
| </span> | ||
| </p> | ||
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| <ul className={listStyle}> | ||
| <li> | ||
| <Label text="Data Integrity Critical" /> When data integrity is | ||
| paramount, and any data loss due to cache failure is unacceptable, | ||
| such as in financial transactions. | ||
| </li> | ||
| <li> | ||
| <Label text="Low Write Frequency" /> In applications where write | ||
| operations are infrequent, the complexity and potential issues of | ||
| write-back caching may not be justified. | ||
| </li> | ||
| <li> | ||
| <Label text="Real-Time Systems" /> For real-time systems where | ||
| immediate data availability and consistency are required, such as live | ||
| trading platforms. | ||
| </li> | ||
| <li> | ||
| <Label text="High Volatility" /> When data changes frequently and | ||
| needs to be immediately reflected across all systems and users, like | ||
| collaborative editing tools. | ||
| </li> | ||
| <li> | ||
| <Label text="Simple Architectures" /> In simpler applications where | ||
| the overhead of managing a write-back cache might outweigh the | ||
| performance benefits. | ||
| </li> | ||
| </ul> | ||
| </> | ||
| ) | ||
| } | ||
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| export default Body |
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| 'use client' | ||
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| import {FC, useEffect, useState} from 'react' | ||
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| import {createGoogleGenerativeAI} from '@ai-sdk/google' | ||
| import {generateText} from 'ai' | ||
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| import Body from './Body' | ||
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| export interface Props { | ||
| component: string | ||
| } | ||
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| const Tags: FC<Props> = ({component}) => { | ||
| const [aiTags, setPromtPresponse] = useState<Array<string>>([]) | ||
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| console.log('Body', Body) | ||
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| useEffect(() => { | ||
| if (aiTags.length > 0) return | ||
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| const google = createGoogleGenerativeAI({ | ||
| apiKey: process.env.NEXT_PUBLIC_GOOGLE_AI_KEY, | ||
| }) | ||
| const model = google('models/gemini-pro') | ||
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| generateText({ | ||
| model, | ||
| prompt: `From the following react component: ${Body} please create five tags. Tags should be return as a plain text seperated with with comma`, | ||
| }).then(response => { | ||
| const tags = response.text.split(',') | ||
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| setPromtPresponse(tags) | ||
| }) | ||
| }, [aiTags]) | ||
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| return <>{aiTags.join(',')}</> | ||
| } | ||
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| export default Tags |