HBaseConAsia2018 Track3-5: HBase Practice at Lianjia

•Download as PPTX, PDF•

2 likes•540 views

This document discusses different big data scenarios using HBase including: 1. Architecture evolution over time including olap and real-time ETL scenarios 2. The olap scenario requirements like handling billion records with sub-second queries and examples using Kylin 3. The monitor scenario showing how different systems are monitored using technologies like Grafana 4. Brief mentions of data mining and HDI scenarios

What's hot

HBaseConAsia2018 Track2-4: HTAP DB-System: AsparaDB HBase, Phoenix, and Spark

Michael Stack

This document discusses using Phoenix and Spark with ApsaraDB HBase. It covers the architecture of Phoenix as a service over HBase, use cases like log and internet company scenarios, best practices for table properties and queries, challenges around availability and stability, and improvements being made. It also discusses how Spark can be used for analysis, bulk loading, real-time ETL, and to provide elastic compute resources. Example architectures show Spark SQL analyzing HBase and structured streaming incrementally loading data. Scenarios discussed include online reporting, complex analysis, log indexing and querying, and time series monitoring.

HBaseConAsia2018 Keynote1: Apache HBase Project Status

Michael Stack

- Apache HBase 2.0.0 is a major new release that was over 4 years in development and focused on compatibility, scale, and performance improvements. - Key changes include a new master region assignment system, off-heap read/write paths, and in-memory compaction. - The goals were to support larger clusters with better resource utilization while fixing issues with the previous master region assignment system.

HBaseConAsia2018 Track3-6: HBase at Meituan

Michael Stack

RedisConf17 - Home Depot - Turbo charging existing applications with Redis

Redis Labs

The Home Depot is transforming its architecture to use microservices and polyglot persistence to handle increasing online order volumes of 250,000 lines per hour. Redis is being used to turbo charge existing monolithic applications by offloading pieces to new processes using patterns like caching, concurrency management, and powering algorithms. This improves performance by reducing database degradation and wait times by over 95%. Next steps include setting up Redis clusters on-premises and off-premises to further reduce database CPU usage and onboard more patterns.

HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase

Michael Stack

This document provides an introduction to JanusGraph, an open source distributed graph database that can be used with Apache HBase for storage. It begins with background on graph databases and their structures, such as vertices, edges, properties, and different storage models. It then discusses JanusGraph's architecture, support for the TinkerPop graph computing framework, and schema and data modeling capabilities. Details are given on partitioning graphs across servers and using different indexing approaches. The document concludes by explaining why HBase is a good storage backend for JanusGraph and providing examples of how the data model would be structured within HBase.

RedisConf17 - Redis Enterprise on IBM Power Systems

Redis Labs

Redis Labs Enterprise Cluster provides a high performance NoSQL data store. It can be deployed on IBM Power Systems servers to take advantage of their high memory bandwidth and cache capabilities. This provides significantly higher performance and lower costs than deploying on x86 servers. Specifically, a Redis Labs cluster on Power Systems can achieve 24x lower infrastructure needs, 2x lower costs, and use 6x less rack space compared to a typical x86 deployment.

Hadoop and HBase @eBay

DataWorks Summit

eBay has one of the largest Hadoop clusters in the industry with many petabytes of data. This talk will give an overview of how Hadoop and HBase have been used within eBay, the lessons we have learned from supporting large-scale production clusters, as well as how we plan to use and improve Hadoop and HBase moving forward. Specific use cases, production issues and platform improvement work will be discussed.

From Kafka to BigQuery - Strata Singapore

Ofir Sharony

Change Data Capture with Data Collector @OVH

Paris Data Engineers !

La collecte de données au sein d'un DataLake sans impacter les systèmes opérationnels est un challenge pour de nombreuses entreprises. Lors du meetup Paris Data Engineers du 26 mars 2019, Dimitri Capitaine nous a présenté Data Collector qui est un outil de Change Data Capture (CDC) développé en interne chez OVH. Data Collector est capable d'assurer une réplication fiable et performante des bases de données jusqu'au DataLake. Hugo Larcher nous a alors présenté un cas d'utilisation autour de l'exploitation de données aéronautiques avec une touche d'IoT et de DataViz.

Redis TimeSeries

Redis Labs

- The document summarizes a meetup about RedisTimeSeries, a time-series data structure for Redis. - RedisTimeSeries allows ingesting large amounts of time-series data at high speeds, performing fast queries with aggregation, and scaling resource efficiency for more users and richer metrics. - Example use cases discussed are infrastructure and services monitoring, caching time-series data to improve performance and reduce costs, and industrial IoT, energy/utilities, and fraud detection applications.

Stsg17 speaker yousunjeong

Yousun Jeong

HBaseCon2017 Apache HBase at Didi

HBaseCon

In DiDi Chuxing Company, which is China’s most popular ride-sharing company. we use HBase to serve when we have a bigdata problem. We run three clusters which serve different business needs. We backported the Region Grouping feature back to our internal HBase version so we could isolate the different use cases. We built the Didi HBase Service platform which is popular amongst engineers at our company. It includes a workflow and project management function as well as a user monitoring view. Internally we recommend users use Phoenix to simplify access.even more,we used row timestamp;multidimensional table schema to slove muti dimension query problems C++, Go, Python, and PHP clients get to HBase via thrift2 proxies and QueryServer. We run many important buisness applications out of our HBase cluster such as ETA/GPS/History Order/API metrics monitoring/ and Traffic in the Cloud. If you are interested in any aspects listed above, please come to our talk. We would like to share our experiences with you.

Hadoop @ eBay: Past, Present, and Future

Ryan Hennig

Redis Tames The Caching Herd: Jon Hyman

Redis Labs

The document summarizes how Braze, a customer engagement platform, optimized their API performance using Redis. Braze saw high API latency and server utilization from cache stampeding when in-app message targeting rules were recomputed every 90 seconds by thousands of requests. To fix this, Braze used Redis to control cache refresh using SETNX locks, extending the cache TTL to 180 seconds with one process refreshing every 90 seconds. This reduced computation concurrency and dropped API requests to 1 per period. Latency stabilized at 3-4 seconds and server count could be reduced, optimizing performance and costs.

The Practice of Presto & Alluxio in E-Commerce Big Data Platform

Alluxio, Inc.

This document discusses JD.com's use of Presto and Alluxio in their big data platform (BDP) architecture. It provides an introduction to Presto and how JD.com uses it in their BDP, including scaling Presto on YARN and using PowerServer for operations and maintenance. It also discusses how Presto and Alluxio are used together to improve query performance through caching and eliminating network traffic. Finally, it outlines ongoing explorations around improving Presto and Alluxio, such as load balancing, resource isolation, supporting larger clusters, and porting HDFS authentication to Alluxio.

Operationalizing Big Data Pipelines At Scale

Databricks

Running a global, world-class business with data-driven decision making requires ingesting and processing diverse sets of data at tremendous scale. How does a company achieve this while ensuring quality and honoring their commitment as responsible stewards of data? This session will detail how Starbucks has embraced big data, building robust, high-quality pipelines for faster insights to drive world-class customer experiences.

Yahoo - Moving beyond running 100% of Apache Pig jobs on Apache Tez

DataWorks Summit

Last year at Yahoo, we spent great effort in scaling, stabilizing and making Pig on Tez production ready and by the end of the year retired running Pig jobs on Mapreduce. This talk will detail the performance and resource utilization improvements Yahoo achieved after migrating all Pig jobs to run on Tez. After successful migration and the improved performance we shifted our focus to addressing some of the bottlenecks we identified and new optimization ideas that we came up with to make it go even faster. We will go over the new features and work done in Tez to make that happen like custom YARN ShuffleHandler, reworking DAG scheduling order, serialization changes, etc. We will also cover exciting new features that were added to Pig for performance such as bloom join and byte code generation. A distributed bloom join that can create multiple bloom filters in parallel was straightforward to implement with the flexibility of Tez DAGs. It vastly improved performance and reduced disk and network utilization for our large joins. Byte code generation for projection and filtering of records is another big feature that we are targeting for Pig 0.17 which will speed up processing by reducing the virtual function calls.

HBaseCon 2015: Apache Kylin - Extreme OLAP Engine for Hadoop

HBaseCon

Kylin is an open source distributed analytics engine contributed by eBay that provides a SQL interface and OLAP on Hadoop supporting extremely large datasets. Kylin's pre-built MOLAP cubes (stored in HBase), distributed architecture, and high concurrency helps users analyze multidimensional queries via SQL and other BI tools. During this session, you'll learn how Kylin uses HBase's key-value store to serve SQL queries with relational schema.

Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...

HostedbyConfluent

The challenge with today’s “data explosion” is finding the most appropriate answer to the question, “So where do I put my data?” while avoiding the longer-term problem: data warehouses, data lakes, cloud storage, NoSQL databases, … are often the places where “big” data goes to die. Enter Physics 101, and my corollary to Newton’s First Law of Motion: Data in motion tends to stay in motion until it comes rest on disk. Similarly, if data is at rest, it will remain at rest until an external “force” puts it in motion again. Data inevitably comes to rest at some point. Without “external forces”, data often gets lost or becomes stale where it lands. “Modern” architectures tend to involve data pipelines where downstream consumers of data make use of data generated upstream, often with built-for-purpose repositories at each stage. This session will explore how data that has come to rest can be put in motion again; how Kafka can keep it in motion longer; and how pipelined architectures might be created to make use of that data.

HBaseConAsia2018 Track1-3: HBase at Xiaomi

Michael Stack

This document summarizes Xiaomi's implementation and use of HBase for data storage. It discusses Xiaomi's HBase clusters across multiple public cloud providers and data centers. It also describes Xiaomi's approaches to multi-tenancy, quota and throttling, synchronous replication between clusters, and high availability in the case of node or cluster failures. Synchronous replication provides stronger consistency guarantees but with some performance overhead compared to asynchronous replication.

What's hot (20)

HBaseConAsia2018 Track2-4: HTAP DB-System: AsparaDB HBase, Phoenix, and Spark

HBaseConAsia2018 Keynote1: Apache HBase Project Status

HBaseConAsia2018 Track3-6: HBase at Meituan

RedisConf17 - Home Depot - Turbo charging existing applications with Redis

HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase

RedisConf17 - Redis Enterprise on IBM Power Systems

Hadoop and HBase @eBay

From Kafka to BigQuery - Strata Singapore

Change Data Capture with Data Collector @OVH

Redis TimeSeries

Stsg17 speaker yousunjeong

HBaseCon2017 Apache HBase at Didi

Hadoop @ eBay: Past, Present, and Future

Redis Tames The Caching Herd: Jon Hyman

The Practice of Presto & Alluxio in E-Commerce Big Data Platform

Operationalizing Big Data Pipelines At Scale

Yahoo - Moving beyond running 100% of Apache Pig jobs on Apache Tez

HBaseCon 2015: Apache Kylin - Extreme OLAP Engine for Hadoop

Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...

HBaseConAsia2018 Track1-3: HBase at Xiaomi

Similar to HBaseConAsia2018 Track3-5: HBase Practice at Lianjia

Cloud-native Semantic Layer on Data Lake

Databricks

Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive

Xu Jiang

Kylin is an open source Distributed Analytics Engine from eBay Inc. that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets. If you want to do multi-dimension analysis on large data sets (billion+ rows) with low query latency (sub-seconds), Kylin is a good option. Kylin also provides seamless integration with existing BI tools (e.g Tableau).

Accelerating Big Data Analytics with Apache Kylin

Tyler Wishnoff

Building Enterprise OLAP on Hadoop for FSI

Luke Han

Apache Kylin Use Cases in China and Japan

Luke Han

Complex Data Transformations Made Easy

Data Con LA

Data Con LA 2020 Description Join this session to learn how to build a modern cloud-scale data compute platform with code in just minutes! Using the industry's first IDE for building data applications, developers can now create data marts and data applications, while working interactively with large datasets. We will explore how easy it is to develop, test and operationalize powerful data compute applications over streaming data using SQL and Python and eager execution in Xcalar with the combination of declarative and visual imperative programming and eager execution You will see how you can reduce time to market for analyzing large volumes of data and building enterprise-level complex data compute applications. You will learn how to increase your developer productivity with SQL and Python, and put your complex business logic and ML models into production pipelines with the fastest time to value in industry. Speaker Nikita Ogievetsky, Xcalar, VP Product Engineering

Apache Kylin @ Big Data Europe 2015

Seshu Adunuthula

The document discusses Apache Kylin, an open source distributed analytics engine that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop for extremely large datasets. It provides an overview of Kylin's features such as sub-second query latency, ANSI SQL support, and seamless integration with BI tools. The document also covers Kylin's architecture, cube storage in HBase, query processing using Calcite, and optimization techniques for cube building.

Eliminating Volatile Latencies Inside Rakuten’s NoSQL Migration

ScyllaDB

Patience with Apache Cassandra’s volatile latencies was wearing thin at Rakuten, a global online retailer serving 1.5B worldwide members. The Rakuten Catalog Platform team architected an advanced data platform – with Cassandra at its core – to normalize, validate, transform, and store product data for their global operations. However, while the business was expecting this platform to support extreme growth with exceptional end-user experiences, the team was battling Cassandra’s instability, inconsistent performance at scale, and maintenance overhead. So, they decided to migrate. Join this webinar to hear a firsthand account of: How specific Cassandra challenges were impacting the team and their product How they determined whether migration would be worth the effort What processes they used to evaluate alternative databases What their migration required from a technical perspective Strategies (and lessons learned) for your own database migration

Keynote -- Percona Live Europe 2018

Kevin Xu

Flink in Zalando's World of Microservices

Zalando Technology

Berlin Apache Flink Meetup, May 2016 In this talk we present Zalando's microservices architecture and introduce Saiki – our next generation data integration and distribution platform on AWS. We show why we chose Apache Flink to serve as our stream processing framework and describe how we employ it for our current use cases: business process monitoring and continuous ETL. We then have an outlook on future use cases. By Javier Lopez & Mihail Vieru, Zalando, Zalando SE

Flink in Zalando's world of Microservices

ZalandoHayley

Apache Flink Meetup at Zalando Technology, May 2016 By Javier Lopez & Mihail Vieru, Zalando In this talk we present Zalando's microservices architecture and introduce Saiki – our next generation data integration and distribution platform on AWS. We show why we chose Apache Flink to serve as our stream processing framework and describe how we employ it for our current use cases: business process monitoring and continuous ETL. We then have an outlook on future use cases.

Apache Kylin Introduction

Luke Han

What's new in Elasticsearch v5

Idan Tohami

[Rakuten TechConf2014] [C-5] Ichiba Architecture on ExaLogic

Rakuten Group, Inc.

IBM Cloud Day January 2021 Data Lake Deep Dive

Torsten Steinbach

This document summarizes an IBM Cloud Day 2021 presentation on IBM Cloud Data Lakes. It describes the architecture of IBM Cloud Data Lakes including data skipping capabilities, serverless analytics, and metadata management. It then discusses an example COVID-19 data lake built on IBM Cloud to provide trusted COVID-19 data to analytics applications. Key aspects included landing, preparation, and integration zones; serverless pipelines for data ingestion and transformation; and a data mart for querying and reporting.

Dataflow in 104corp - AWS UserGroup TW 2018

Gavin Lin

This document discusses migrating data processing workflows from on-premises to cloud-based serverless architectures. It outlines reasons for upgrading systems like HDFS and Pig to cloud services including AWS EMR, Kinesis, and S3 for improved resource utilization, high availability, and performance. The document then details considerations for how to migrate components like streaming, storage, computing, exploration and serving to various AWS services, and concludes with recommendations to leverage AWS services where possible for ease of use while balancing controllability and cost versus performance.

PCM18 (Big Data Analytics)

Stratebi

Webinar: Unlock the Power of Streaming Data with Kinetica and Confluent

Kinetica

The volume, complexity and unpredictability of streaming data is greater than ever before. Innovative organizations require instant insight from streaming data in order to make real-time business decisions. A new technology stack is emerging as traditional databases and data lakes are challenged to analyze streaming data and historical data together in real time. Confluent Platform, a more complete distribution of Apache Kafka®, works with Kinetica’s GPU-accelerated engine to transform data on the wire, instantly ingest data and analyze it at the same time. With the Kinetica Connector, end users can ingest streaming data from sensors, mobile apps, IoT devices and social media via Kafka into Kinetica’s database to combine it with data at rest. Together, the technologies deliver event-driven and real-time data to power the speed of thought analytics, improve customer experience, deliver targeted marketing offers and increase operational efficiencies.

Apache Kylin Extreme OLAP Engine for Big Data

Luke Han

This document provides an overview of Apache Kylin, an open source distributed analytics engine that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets. It discusses Kylin's features such as fast query performance, SQL interface, seamless integration with BI tools, and job management capabilities. It also describes Kylin's technical architecture including its use of MapReduce for cube building, storage of cubes in HBase, and routing of SQL queries to the query engine. The document outlines Kylin's roadmap including plans to improve cube building algorithms and support real-time analysis using streaming and Spark.

Apache kylin - Big Data Technology Conference 2014 Beijing

Luke Han

This document provides an overview of Apache Kylin, an open source distributed analytics engine from eBay that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets. Key points include: Kylin is designed to accelerate analytics queries on billions of rows of data on Hadoop; it provides ANSI SQL, full OLAP capability, and seamless integration with BI tools; and performance tests show it can return results over 100x faster than Hive for both high-level and drill-down queries.

Similar to HBaseConAsia2018 Track3-5: HBase Practice at Lianjia (20)

Cloud-native Semantic Layer on Data Lake

Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive

Accelerating Big Data Analytics with Apache Kylin

Building Enterprise OLAP on Hadoop for FSI

Apache Kylin Use Cases in China and Japan

Complex Data Transformations Made Easy

Apache Kylin @ Big Data Europe 2015

Eliminating Volatile Latencies Inside Rakuten’s NoSQL Migration

Keynote -- Percona Live Europe 2018

Flink in Zalando's World of Microservices

Flink in Zalando's world of Microservices

Apache Kylin Introduction

What's new in Elasticsearch v5

[Rakuten TechConf2014] [C-5] Ichiba Architecture on ExaLogic

IBM Cloud Day January 2021 Data Lake Deep Dive

Dataflow in 104corp - AWS UserGroup TW 2018

PCM18 (Big Data Analytics)

Webinar: Unlock the Power of Streaming Data with Kinetica and Confluent

Apache Kylin Extreme OLAP Engine for Big Data

Apache kylin - Big Data Technology Conference 2014 Beijing

More from Michael Stack

hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud

Michael Stack

hbaseconasia2019 Recent work on HBase at Pinterest

Michael Stack

hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd

Michael Stack

hbaseconasia2019 HBase at Didi

Michael Stack

hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...

Michael Stack

hbaseconasia2019 HBase at Tencent

Michael Stack

hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...

Michael Stack

hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...

Michael Stack

hbaseconasia2019 Pharos as a Pluggable Secondary Index Component

Michael Stack

hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba

Michael Stack

hbaseconasia2019 OpenTSDB at Xiaomi

Michael Stack

hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark

Michael Stack

hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase

Michael Stack

hbaseconasia2019 Distributed Bitmap Index Solution

Michael Stack

hbaseconasia2019 HBase Bucket Cache on Persistent Memory

Michael Stack

hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL

Michael Stack

hbaseconasia2019 BDS: A data synchronization platform for HBase

Michael Stack

hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...

Michael Stack

hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...

Michael Stack

The document discusses HBCK2, a tool for fixing issues in HBase 2. Some key points: 1. HBCK2 is simpler than HBCK1, with fewer fix commands and no diagnosis commands. It requires a deeper understanding of HBase internals. 2. HBCK2 commands are master-oriented and fix issues one at a time. Common issues include regions not online, stuck procedures, and tables in the wrong state. 3. Recipes are provided to fix specific issues like missing meta regions or regions in transition using HBCK2 commands like assigns and bypass. 4. HBCK2 is still a work in progress but contributions are welcome

HBaseConAsia2019 Keynote

Michael Stack

More from Michael Stack (20)

hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud

hbaseconasia2019 Recent work on HBase at Pinterest

hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd

hbaseconasia2019 HBase at Didi

hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...

hbaseconasia2019 HBase at Tencent

hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...

hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...

hbaseconasia2019 Pharos as a Pluggable Secondary Index Component

hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba

hbaseconasia2019 OpenTSDB at Xiaomi

hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark

hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase

hbaseconasia2019 Distributed Bitmap Index Solution

hbaseconasia2019 HBase Bucket Cache on Persistent Memory

hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL

hbaseconasia2019 BDS: A data synchronization platform for HBase

hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...

hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...

HBaseConAsia2019 Keynote

Recently uploaded

How Can Microsoft Office 365 Improve Your Productivity?

Digital Host

Microsoft Office 365 is a cloud-based subscription service offering essential productivity tools. It includes Word for documents, Excel for data analysis, PowerPoint for presentations, Outlook for email, OneDrive for cloud storage, and Teams for collaboration. Key benefits are accessibility from any device, advanced security, and regular updates. Office 365 enhances collaboration with real-time co-authoring and Teams, streamlines communication with Outlook and Teams Chat, and improves data management with OneDrive and SharePoint. For reliable office 365 hosting, Digital Host offers various subscription plans, setup support, and training resources. Visit https://www.digitalhost.com/email-office/office-365/

The Money Wave 2024 Review: Is It the Key to Financial Success?

nirahealhty

What is The Money Wave? The Money Wave is a wealth manifestation software designed to help individuals attract financial abundance through audio tracks. Created by James Rivers, this program uses scientifically-backed methods to improve cognitive functions and reduce stress, thereby enhancing one's ability to manifest wealth. How Does The Money Wave Audio Program Work? The Cash Wave program works by utilizing the force of sound frequencies to overhaul your cerebrum. These audio tracks are designed to promote deep relaxation and improve cognitive functions. The underlying science suggests that specific sound waves can influence brain activity, leading to enhanced problem-solving abilities and reduced stress levels. How to Use The Money Wave Program? Using The Money Wave program is straightforward: Download the Audio Tracks: Once purchased, you can download the audio files from the official website. Listen Daily: For best results, listen to the tracks daily. Consistency is key. Relax and Visualize: Find a quiet place, relax, and visualize your financial goals as you listen. Follow the Guide: The program includes a detailed guide to help you maximize the benefits.

Do it again anti Republican shirt Do it again anti Republican shirt

exgf28

ADEGUNADEGUNADEGUNADEGUNADEGUNADEGUNADEGUN.pdf

ifraghaffar125

How God led me to DTS? Through many different signs and connections that I c...

AshishMohan57

Latest Deals in the Metaverse & NFT Markets.docx

SFC Today

How to Become a Digital Marketer in 2024.docx

InfyQ Seo Experts

In today's digital world, digital marketers are indispensable. They play a crucial role in helping businesses connect with their audiences effectively through various online channels. Whether you're considering a career change or aiming to advance in the field, here’s a detailed guide to thriving as a digital marketer in 2024. Why Choose Digital Marketing? Digital marketing encompasses a wide array of strategies aimed at engaging and converting online audiences. From optimizing websites for search engines to crafting compelling social media campaigns and leveraging data analytics, digital marketers drive business growth and enhance brand visibility in the digital sphere. Essential Skills for Success To excel in digital marketing, mastering a diverse skill set is essential: 1. SEO (Search Engine Optimization) Understanding Search Engine Optimization principles is vital for enhancing a website's visibility in search engine results. This includes keyword research, on-page optimization techniques, and building authoritative backlinks to boost organic traffic. 2. PPC (Pay-Per-Click) Advertising PPC advertising involves placing targeted ads on search engines and social media platforms, paying only when users click. Proficiency in platforms like Google Ads and Facebook Ads, along with strategic bidding and ad copywriting skills, is crucial for maximizing campaign ROI. 3. Social Media Marketing Social media platforms serve as powerful tools for engaging with audiences and building brand loyalty. Effective social media marketers understand platform nuances, create engaging content, and utilize analytics to refine strategies and drive meaningful engagement. 4. Content Marketing Content marketing revolves around creating valuable, relevant content that attracts and retains target audiences. This includes blog posts, videos, infographics, and eBooks tailored to resonate with audience interests and needs. 5. Email Marketing Email marketing remains an effective channel for nurturing leads and maintaining customer relationships. Skills in crafting personalized campaigns, segmenting audiences, and analyzing email performance metrics are essential for optimizing campaign effectiveness. 6. Analytics and Data Interpretation Data-driven decision-making is pivotal in digital marketing success. Proficiency in tools like Google Analytics enables marketers to track website traffic, user behavior, and campaign performance, providing actionable insights to drive continuous improvement.

Module 16 Incineration of Healthcare Waste and the Stockholm Convention Guide...

Beshoelwy

New York Institute of Technology degree Cert diploma offer

ubovu

定制留信网认证Cert【微信：176555708】【NYIT��业证（纽约理工大学毕业证）成绩单offer】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致��于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：176555708】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：176555708】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份【微信：176555708】 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才 → 【关于价格问题（保证一手价格）我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们��会适当给一些优惠。选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！办理纽约理工大学毕业证（NYIT毕业证【微信：176555708】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。办理纽约理工大学毕业证（NYIT毕业证【微信：176555708】格式相对统一，各专业都有相应的模板。通常包括以下部分：校徽：象征着学校的荣誉和传承。校名:学校英文全称授予学位：本部分将注明获得的具体学位名称。毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。办理纽约理工大学毕业证（NYIT毕业证【微信：176555708】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。综上所述，办理纽约理工大学毕业证（NYIT毕业证【微信：176555708 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

The Ultimate Guide to Web Hosting Reviews in 2024.pdf

Hosting Mastery Hub

Choosing the right web hosting provider can be a daunting task, especially with the plethora of options available. To help you make an informed decision, we’ve compiled comprehensive reviews of some of the top web hosting providers for 2024, with a special focus on Hosting Mastery Hub. This guide will cover the features, pros, cons, and unique offerings of each provider. By the end, you’ll have a clearer understanding of which hosting service best suits your needs.

The Money Wave 2024 Review_ Is It the Key to Financial Success.pdf

nirahealhty

What is The Money Wave? The Money Wave is a comprehensive financial program designed to equip individuals with the knowledge and tools necessary for achieving financial independence. It encompasses a range of resources, including educational materials, webinars, and community support, all aimed at helping users understand and leverage various financial opportunities. ➡️ Click here to get The Money Wave from the official website. Key Features of The Money Wave Educational Resources: The Money Wave offers a wealth of educational materials that cover essential financial topics, including budgeting, investing, and wealth-building strategies. These resources are designed to empower users with the knowledge needed to make informed financial decisions. Expert Guidance: Users gain access to insights from financial experts who share their experiences and strategies for success. This guidance can be invaluable for individuals looking to navigate the complexities of personal finance. Community Support: The program fosters a supportive community where users can connect with like-minded individuals. This network provides encouragement, accountability, and shared experiences that can enhance the learning process. Actionable Strategies: The Money Wave emphasizes practical, actionable strategies that users can implement immediately. This focus on real-world application sets it apart from other financial programs that may be more theoretical in nature. Flexible Learning: The program is designed to accommodate various learning styles and schedules. Users can access materials at their convenience, making it easier to integrate financial education into their daily lives. Benefits of The Money Wave Increased Financial Literacy: One of the primary benefits of The Money Wave is the enhancement of financial literacy. Users learn essential concepts that enable them to make better financial decisions, ultimately leading to improved financial health. Empowerment: By providing users with the tools and knowledge needed to take control of their finances, The Money Wave empowers individuals to take proactive steps toward achieving their financial goals. Networking Opportunities: The community aspect of The Money Wave allows users to connect with others who share similar financial aspirations. This network can lead to valuable partnerships, collaborations, and support systems. Long-Term Success: The strategies taught in The Money Wave are designed for long-term success. Users are encouraged to adopt a mindset of continuous learning and growth for sustained financial well-being. Accessibility: With its online format, The Money Wave is accessible to anyone with an internet connection. This inclusivity allows individuals from various backgrounds to benefit from the program.

Java Training in Chandigarh.Mastering Java: From Fundamentals to Advanced App...

aryan4bhardwaj37

Excel in Java Programming with Excellence Academy‘s top-notch Best Java training & Certification in Chandigarh. Immerse yourself in 100% practical training on live projects from global clients in the USA, UK, France, and Germany. Our comprehensive program covers the development of dynamic web applications, emphasizing Java, Servlets, JSP, Spring, and more. Whether pursuing a full-time one-year diploma or a short-term course, Excellence Academy offers a 2-year validity for your Java programming journey. Our Java training is the gateway to mastering programming languages and building robust, scalable applications. So enroll now the Java Complete Course For Beginners.

High-Yield Dow Jones Stocks Worth Investing in Today.docx

SFC Today

Recently uploaded (13)

How Can Microsoft Office 365 Improve Your Productivity?

The Money Wave 2024 Review: Is It the Key to Financial Success?

Do it again anti Republican shirt Do it again anti Republican shirt

ADEGUNADEGUNADEGUNADEGUNADEGUNADEGUNADEGUN.pdf

How God led me to DTS? Through many different signs and connections that I c...

Latest Deals in the Metaverse & NFT Markets.docx

How to Become a Digital Marketer in 2024.docx

Module 16 Incineration of Healthcare Waste and the Stockholm Convention Guide...

New York Institute of Technology degree Cert diploma offer

The Ultimate Guide to Web Hosting Reviews in 2024.pdf

The Money Wave 2024 Review_ Is It the Key to Financial Success.pdf

Java Training in Chandigarh.Mastering Java: From Fundamentals to Advanced App...

High-Yield Dow Jones Stocks Worth Investing in Today.docx

HBaseConAsia2018 Track3-5: HBase Practice at Lianjia

1. hosted by Hbase Practice At ke.com Guoxian Zhao

2. hosted by Content 01 02 04 03 Architecture Evolution Olap Scenario Monitor Scenario Data Mining Scenario 05 Reatime ETL Scenario 06 Hdic Scenario

3. hosted by Architecture Evolution01

4. hosted by bigdata architecture for ke Evolution

5. hosted by Olap Scenario02

6. hosted by Olap Scenario Requirement List Billion data set subsecond response times High concurrency sql interface

7. hosted by Olap Scenario kylin

8. hosted by Olap data architecture map permission Olap Scenario monitor meta scheduler Hbase … hadoop, warehouse + compute … load Alluxio Sparksql Spark cluster presto queryengine adhoc build zk build nginx query query Offline kylin Kylin middleware query Meta manager Cube execute Statistics redis redisMetrics api product

9. hosted by Data For Kylin  800+cube、16+business  200T storage、160000 million data、1 cube 6000 million  Query/day million， <500ms(95%), <1s (99%)

10. hosted by Data Product Metrics platform • roll-up drill • multidimensional analysis • self-service configuration report • standard indices

11. hosted by Performance Optimizations For Hbase SSD-FIRST • Read remote ssds first Client H D D S S D H D D DN1 DN2 DN3 OR

12. hosted by Performance Optimizations For Hbase others  HDFS short-circuit  Data hedged ，multi thread read  Test stale datanodes, avoid the slow datanode  Shutdown balance  Multiwal， Improve write performance

13. hosted by Monitor Scenario03

14. hosted by Monitor senario HAProxy TeleGraf Task metrics Hadoopmetric s TSD TSD HBASE grafana

15. hosted by Monitor Scenario

16. hosted by Data Mining Scenario04

17. hosted by Data Mining Scenario

18. hosted by RealTime ETL Scenario05

19. hosted by RealTime ETL Scenario Subtitle Text RealTime DB ETL RealTime log ETL 3 4 HBASE fast write fast read change record bigdata storage

20. hosted by Hdic Scence06

21. hosted by Hdic Scenario Subtitle Text 3 4

22. hosted by Data For Ke

23. hosted by Thanks