explain why Kelvin waves propagate with the coast on the left in the southern hemisphere?
时间: 2024-05-31 20:08:05 浏览: 13
Kelvin waves are a type of ocean wave that is caused by changes in ocean currents and temperatures. In the southern hemisphere, the Coriolis effect causes the water to move to the left of the direction of the wave's propagation. This means that the wave will appear to be moving with the coast on the left. This is because the Coriolis effect deflects the water to the left, which creates a pressure gradient that causes the wave to move in that direction. This effect is opposite in the northern hemisphere, where the water is deflected to the right and the wave appears to move with the coast on the right.
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What is mapreduce ? Explain the functions of mapper and reducer with example
MapReduce is a programming model and software framework for processing large sets of data in a distributed and parallel manner. It allows for processing of large data sets on clusters of computers using a simple model for parallel processing.
In the MapReduce framework, the input data is divided into chunks and each chunk is processed by a separate mapper function. The mapper function processes the input data and generates intermediate key-value pairs. These key-value pairs are then sorted and grouped by key, and passed on to the reducer function. The reducer function then aggregates the intermediate key-value pairs and generates a final output.
For example, let's say we have a large data set of customer orders that we want to process using MapReduce. The mapper function will read each order and generate intermediate key-value pairs where the key is the customer ID and the value is the order amount. The intermediate key-value pairs might look like this:
```
customer1: 10.99
customer2: 25.55
customer1: 5.99
customer3: 15.00
customer2: 12.50
```
These intermediate key-value pairs are then sorted and grouped by key:
```
customer1: [10.99, 5.99]
customer2: [25.55, 12.50]
customer3: [15.00]
```
The reducer function then aggregates the values for each key and generates a final output:
```
customer1: 16.98
customer2: 38.05
customer3: 15.00
```
In this example, the MapReduce framework allowed us to process a large data set in a distributed and parallel manner, making it faster and more efficient.
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Space exploration is important for several reasons. Firstly, it allows us to learn more about the universe and how it works, which can help us understand our place in it. Secondly, it allows us to search for extraterrestrial life and to study planets like Mars for potential colonization or resource extraction. Thirdly, space exploration has a significant impact on technological advancement and innovation, leading to spin-off technologies that can benefit society in a variety of ways.
Mars exploration, in particular, has received a great deal of attention in recent years due to its potential for supporting human life. Scientists believe that Mars once had a more Earth-like environment and may have supported microbial life in the past. Studying Mars can help us better understand the conditions necessary for life to exist and how we might create those conditions on other planets in the future.
In addition, Mars has the potential to serve as a location for human settlement or resource extraction. Mars contains a variety of minerals and resources that could be valuable in future space exploration or even back on Earth. Colonizing Mars would also provide backup for human civilization in the event of a catastrophic event on Earth.
Overall, space exploration, and Mars exploration in particular, are crucial for advancing our understanding of the universe and our place in it, discovering potential extraterrestrial life, and laying the foundation for future human settlement and resource extraction.