2025 대학수학능력시험 9월 모의평가 듣기 16-17

Good morning, students. Today, we’re going to learn about the key characteristics that enable some animals to reach high speeds. First, there’s no animal faster on land than the cheetah. Its flexible backbone and joints allow for extreme extension, enabling it to stretch its legs very far and push off its back legs with great force like a spring. Second, the falcon is one of the fastest birds. Its large breastbone allows more muscle to be attached to it, so it can beat its wings with greater power. Third, the swordfish is among the fastest fish in the sea. It releases a special, slippery oil from its head that coats the front of its body, enabling it to swim with less resistance. Lastly, the dragonfly is considered the world’s fastest flying insect. It has the unique ability to slightly twist its wings as they swing down, causing a small tornado-like wind that gives it a boost of speed. Now, let’s watch a video of nature’s speedsters.
*breastbone: 흉골, 가슴뼈 
*coat: ~에 칠하다, 웃옷을 입히다

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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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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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Install and run an FTP server using Docker

To install and run an FTP server using Docker, follow these steps. We’ll use the popular stilliard/pure-ftpd image, which is a lightweight and widely used FTP server. Step 1: Install Docker Make sure Docker is installed on your machine. If it isn’t, install it using the instructions below: Ubuntu/Debian: sudo apt update sudo apt install docker.io -y Mac: Install Docker Desktop from Docker's website . Windows: Install Docker Desktop from Docker's website . Verify Docker is installed: docker --version Step 2: Pull the FTP Server Docker Image Use the stilliard/pure-ftpd image, which is a simple and effective FTP server. docker pull stilliard/ pure -ftpd Step 3: Run the FTP Server Run the FTP server container using the following command: docker run -d --name ftp-server \ - p 21 : 21 -p 30000 - 30009 : 30000 - 30009 \ - e FTP_USER_NAME=testuser \ - e FTP_USER_PASS=testpass \ - e FTP_USER_HOME= /home/testuser \ stilliard/pure-ftpd Explanation...
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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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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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dagrun_timeout of Airflow

In Apache Airflow, you can set a timeout for an entire DAG run using the dagrun_timeout parameter in the DAG definition. This parameter allows you to specify the maximum amount of time a DAG run is allowed to execute. If the DAG run exceeds this time limit, it will be marked as failed, and all running tasks in that run will be terminated. Setting dagrun_timeout Here's how to set a timeout for a DAG run: from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from datetime import datetime, timedelta # Define the DAG with DAG( 'my_dag_with_timeout', description='A DAG with a run timeout', schedule_interval='@daily', start_date=datetime(2023, 1 , 1 ), catchup=False, dagrun_timeout=timedelta(hours=2) # Set a 2-hour timeout for the entire DAG run ) as dag: # Define tasks start = DummyOperator( task_id='start') end = DummyOperator( task_id='end') # Define ta...
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MAX_POLL_RECORDS_CONFIG in Kafka

The default value of MAX_POLL_RECORDS_CONFIG in Apache Kafka is: 500 What is MAX_POLL_RECORDS_CONFIG ? The MAX_POLL_RECORDS_CONFIG configuration specifies the maximum number of records a Kafka consumer can retrieve in a single call to the poll() method. Key Details: Default Behavior : If not configured, the consumer will fetch up to 500 records per poll. This is a batch size limit and helps in controlling the volume of data processed at a time. Adjusting the Value : Smaller values (e.g., 10 ): Useful for low-latency processing or when you want to process fewer records at a time. Larger values (e.g., 1000 ): Useful for batch processing or applications designed to handle high throughput. Use Case Scenarios : High throughput: Increase the value to minimize the number of poll() calls. Low latency or real-time processing: Decrease the value to process smaller chunks faster. Example Configuration Java Configuration: Properties props = new Properties(); p...
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How to change java version on gradle of flutter

To change the Java version used by Gradle in a Flutter project, you need to modify the build.gradle files of your Flutter project. Here's how you can do that: Steps: Locate the build.gradle files: You will find two build.gradle files in your Flutter project: One at the root level: <project_root>/android/build.gradle Another inside the app module: <project_root>/android/app/build.gradle Update the Java version in android/build.gradle : In the root build.gradle file, ensure that the sourceCompatibility and targetCompatibility settings are set to the desired Java version. Open <project_root>/android/build.gradle Look for the compileOptions block (or create it if it's not present). Update the Java version like this: allprojects { repositories { google() mavenCentral() } } subprojects { afterEvaluate { project -> if ( project .hasProperty( "android" )) { android { ...
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Comparison of avro plugin

Great question! Both com.github.davidmc24.gradle.plugin.avro and com.commercehub.gradle.plugin.avro are Gradle plugins used for integrating Avro schema compilation into a Java project. However, they have some key differences, and choosing the right one depends on your use case and preferences. Comparison: Aspect com.github.davidmc24.gradle.plugin.avro com.commercehub.gradle.plugin.avro Latest Activity / Maintenance Actively maintained (as of my cutoff date, 2021). CommerceHub's plugin has been largely stable but less actively maintained. Community Usage Growing popularity, newer alternative to CommerceHub's plugin. More widely used for legacy projects. Gradle Plugin Portal Available and regularly updated. Also available, but less frequent updates. Configuration Style Simpler, more modern Kotlin DSL support. Slightly more complex with some legacy design choices. Features Offers a clean interface with support for advanced options (like per-task...
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To build a gRPC service with Gradle, Java, and Avro

To build a gRPC service with Gradle , Java , and Avro , follow these steps. This example will walk you through creating a basic user data service that allows clients to send and retrieve user information. Project Structure grpc-avro-user-service/ │ ├── src/ │ ├── main/ │ │ ├── avro/ │ │ │ └── user .avsc │ │ ├── java/ │ │ │ ├── proto/ │ │ │ │ └── UserService .proto │ │ │ └── com/example/userservice/ │ │ │ ├── UserServiceImpl .java │ │ │ └── App .java ├── build .gradle └── settings.gradle Step-by-Step Guide 1. Define the Avro Schema ( user.avsc ) Create an Avro schema for user data, which will be serialized and used by the service. src/main/avro/user.avsc : { "namespace" : "com.example.userservice" , "type" : "record" , "name" : "User" , "fields" : [ { "name" : "id" , "type" : "string" }, { ...
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