Jack Ma, 马云(馬雲), 마윈

 





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Fundamentals of English Grammar #1

That's a great textbook table of contents! It covers the fundamental tenses in English. Here is a summary of the highlighted sections, with example sentences and key learning tips. PRESENT TIME Item Topic Example Sentence(s) Learning Summary 1-1 The simple present and the present progressive Simple Present: The sun rises in the east. (Fact/Habit) / Present Progressive: She is studying for her exam right now. (Action in progress) Simple Present is for facts, habits, and routines . Present Progressive is for actions happening at the moment of speaking or temporary situations . 1-3 Frequency adverbs I always drink coffee in the morning. / He is never late for class. These adverbs ( always, usually, often, sometimes, rarely, never ) describe how often an action occurs. Their position is key: before the main verb, but after the verb to be or auxiliary verbs. 1-4, 1-5 Final -s / Spelling of final -s/-es He read s a book. / She watch es TV. The final -s (or -es ) is adde...
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Create topic on Kafka with partition count, 카프카 토픽 생성하기

To create a Kafka topic with 100 partitions, you can use the Kafka command-line tool ( kafka-topics.sh or kafka-topics.bat for Windows). When creating a topic, you can specify the number of partitions and the replication factor. Here’s how to create a topic with 100 partitions: Step-by-step instructions: Open a terminal on your machine where Kafka is installed. Run the kafka-topics.sh command with the necessary options to create the topic: kafka - topics . sh - - create - - bootstrap - server localhost:9092 - - replication - factor 1 - - partitions 100 - - topic < topic_name > --bootstrap-server localhost:9092 : Specifies the Kafka broker (or cluster) address. Replace localhost:9092 with your actual Kafka broker address if it’s different. --replication-factor 1 : Specifies the number of replicas for each partition. In this example, it's set to 1 , but in a production environment, you’ll want a higher replication factor for redundancy. --partitions 10...
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To download a file from MinIO using Spring Boot, 스프링부트 Minio 사용하기

To download a file from MinIO using Spring Boot, you can utilize the MinIO Java SDK. Here's an example of how you can achieve this: Add the MinIO dependency to your pom.xml file: < dependency > < groupId > io.minio </ groupId > < artifactId > minio </ artifactId > < version > 7.1.0 </ version > </ dependency > Create a configuration file (e.g., MinioConfig.java ) to establish a connection with your MinIO server: ```java import io.minio.MinioClient; import org.springframework.beans.factory.annotation.Value; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; @Configuration public class MinioConfig { @Value( " ${minio.endpoint} " ) private String endpoint; @Value( " ${minio.accessKey} " ) private String accessKey; @Value( " ${minio.secretKey} " ) private String secretKey; @Bean public MinioClient minioClient() { re...
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Vespa vs Milvus

Vespa and Milvus are both powerful open-source vector search engines, but they differ significantly in terms of architecture, features, and use cases. Here's a comparison of the two: 1. Overview Vespa : Type : Distributed Search Engine Primary Focus : Full-text search, recommendation systems, machine learning, and vector search. Use Cases : eCommerce, news, social media, personalized recommendations, and general search. Key Strengths : Scalable, handles both structured and unstructured data, supports complex queries (e.g., multi-field search, ranking, aggregations). Milvus : Type : Vector Database and Search Engine Primary Focus : Efficient similarity search for high-dimensional vectors (commonly used in machine learning, AI, and computer vision tasks). Use Cases : AI-driven applications, image search, video search, recommendation engines based on embeddings, NLP, and other ML-based tasks. Key Strengths : Optimized for vector search, handles billions of vectors wi...
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Scan an HBase table with a prefix filter

To scan an HBase table with a prefix filter , you can either use the HBase shell , Java API , or Python via HappyBase . The prefix filter helps to retrieve only the rows whose row keys start with a specific prefix . Below are different ways to perform this operation. 1. Using HBase Shell In the HBase shell , you can use the scan command along with a filter expression to scan rows based on a prefix. Example: hbase (main) : 001 : 0 > scan 'table_name' , {FILTER => "PrefixFilter('prefix_value')" } Explanation: Replace 'table_name' with the name of your HBase table. Replace 'prefix_value' with the prefix you want to search for in the row keys. This filter ensures that only rows whose row keys start with the given prefix are retrieved. 2. Using Java API (HBase Client) If you're working in Java, you can use the PrefixFilter class from the HBase API to scan the table. Example: import org.apache.hadoop.hbase.client.*;...
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Using the MinIO API via curl

Using the MinIO API via curl is straightforward, as MinIO is compatible with Amazon S3 API, so most commands follow a similar syntax. Here’s a guide on how to use curl with the MinIO API for some common operations like uploading, downloading, and managing objects. Prerequisites Access Key and Secret Key : Obtain your MinIO Access Key and Secret Key. MinIO Endpoint : Know your MinIO server endpoint, e.g., http://localhost:9000 . Bucket : You may need an existing bucket name, or create a new one using the commands below. Authentication Header For requests to work with MinIO, you need to include authentication in the headers. MinIO uses AWS Signature Version 4 for signing requests. Common Examples 1. List Buckets To list all buckets in your MinIO account, use: curl -X GET \ - -url "http://localhost:9000/" \ - H "Authorization: AWS <AccessKey>:<Signature>" 2. Create a Bucket To create a new bucket, use: curl -X PUT \ - -url "htt...
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In HBase, the "memory to disk" flush operation

In HBase, the "memory to disk" flush operation (or "memstore flush") happens when data in the memstore (in-memory storage) is flushed to disk as HFiles in HDFS. This flush can occur based on multiple triggers rather than a strict time interval, including: Memstore Size Limit : The primary trigger is when the size of the memstore reaches a defined threshold. The default maximum memstore size per RegionServer is set by the configuration parameter hbase.regionserver.global.memstore.size , typically as a fraction of the total heap size. When the memstore fills up, it triggers an automatic flush to disk. Time-Based Flush (Optional) : Although time-based flushes are not the main flush trigger, HBase provides an optional parameter for a maximum delay, which can ensure that data gets written to disk within a certain time, even if the memstore size limit hasn't been reached. This parameter is: hbase.hregion.memstore.flush.period : This sets the maximum time (in mil...
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To switch to a specific tag in a Git repository

To switch to a specific tag in a Git repository, you can use the git checkout or git switch command. Here's how you can do it: 1. List Available Tags First, you may want to see a list of all available tags in the repository: git tag 2. Checkout a Specific Tag Once you know the tag you want to switch to, you can use either git checkout or git switch (if you're using a newer version of Git, which recommends git switch for checking out branches). Using git checkout : git checkout <tag- name > Using git switch (recommended for newer versions of Git): git switch -- detach <tag- name > The --detach flag is necessary because tags are not branches; they are just pointers to specific commits. Using --detach makes your HEAD point to the tag without modifying any branch. 3. Verify the Checkout After switching to the tag, verify that you're on the correct commit: git status This will show the tag you're currently on (you'll see somethi...
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kafka polling vs listen

In Kafka, polling and listening are two different approaches to consuming messages, and they correspond to different APIs or frameworks. 1. Kafka Polling Polling refers to the use of Kafka's native poll() method in the Kafka Consumer API . It requires the consumer application to actively request messages from Kafka. Key Characteristics: Active Consumption : The application explicitly calls poll() in a loop to fetch messages. Manual Commit : Developers can choose when to commit offsets, giving fine-grained control over processing and checkpointing. Use Case : Recommended for applications where control over message consumption, offset management, or threading is critical. Example (Java): Properties props = new Properties(); props . put (ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092" ); props . put (ConsumerConfig.GROUP_ID_CONFIG, "group1" ); props . put (ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest" ); props . ...
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Joining an additional control plane node to an existing Kubernetes cluster

Joining an additional control plane node to an existing Kubernetes cluster involves specific steps to ensure proper synchronization between the control plane components. Below is the detailed process: 1. Pre-Requisites Ensure the following on the new control plane node: Same Kubernetes Version : The new node must have the same Kubernetes version installed as the existing control plane. kubeadm version Kubeadm, Kubelet, and Kubectl Installed : Ensure these tools are installed and configured. Network Configuration : The new control plane must have network connectivity to the existing control plane nodes. 2. Retrieve the Join Command On an existing control plane node, generate the kubeadm join command with the --control-plane flag: kubeadm token create -- print -join-command You will get output similar to: kubeadm join <control-plane-endpoint> : 6443 --token <token> \ --discovery-token- ca -cert-hash sha256 : <hash> \ --control-plane 3. ...
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