system-design | Preparing for system design interview questions | DB Client library
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Preparing for system design interview questions
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system-design Examples and Code Snippets
Lines of Code : 24License : Non-SPDX
Copydef set(self, results, query):
"""Set the result for the given query key in the cache.
When updating an entry, updates its position to the front of the LRU list.
If the entry is new and the cache is at capacity, removes the o def deal_card(self):
try:
card = self.cards[self.deal_index]
card.is_available = False
self.deal_index += 1
except IndexError:
return None
return card def __init__(self, operators, supervisors, directors):
self.operators = operators
self.supervisors = supervisors
self.directors = directors
self.queued_calls = deque() Community Discussions
Trending Discussions on system-design
QUESTION
I'm reading an online document that explains how to design a url shortening service. The website is https://www.educative.io/courses/grokking-the-system-design-interview .
In the section, Encoding actual URL, they said -> "We can compute a unique hash (e.g., MD5 or SHA256, etc.) of the given URL. The hash can then be encoded for displaying. This encoding could be base36 ([a-z ,0-9]) or base62 ([A-Z, a-z, 0-9]) and if we add ‘+’ and ‘/’ we can use Base64 encoding. A reasonable question would be, what should be the length of the short key? 6, 8, or 10 characters."
"If we use the MD5 algorithm as our hash function, it’ll produce a 128-bit hash value. After base64 encoding, we’ll get a string having more than 21 characters (since each base64 character encodes 6 bits of the hash value).Since we only have space for 8 characters per short key, how will we choose our key then? We can take the first 6 (or 8) letters for the key. This could result in key duplication, to resolve that, we can choose some other characters out of the encoding string or swap some characters."
I used online MD5 hash generator (http://onlinemd5.com/) and Base64 encoder (https://www.base64encode.org/) to verify the above. I used "www.yahoo.com" as the input string for MD5 hash and output is 1B03577ED104F16AADC00A639D33CB44 . Then I Base64 encoded it and got MUIwMzU3N0VEMTA0RjE2QUFEQzAwQTYzOUQzM0NCNDQ= with UTF-8 destination charset and Unix newline seperator.
Can anyone explain if I'm doing it correctly? I see the number of characters are way more than 21.
...ANSWER
Answered 2020-Jan-11 at 07:40The problem is that you are using the output of MD5 as a string of hexadecimal digits, and then base64 encoding that string. There's no reason to base64 encode that string - base64 encoding is intended for binary data. What you probably wanted to do is base64 the actual 128-bit binary value of the MD5 hash. Here is some Python code that does what I think you are trying to do:
QUESTION
I'm looking at donne martin's design for a web crawler. the crawler service processes a newly crawled url, and then:
- Adds a job to the Reverse Index Service queue to generate a reverse index
- Adds a job to the Document Service queue to generate a static title and snippet
what would happen if instead the crawler service would synchronously call these 2 services? I would still be able to horizontally scale all 3 services according to the load on each, right? what came to me as a possible reason is just more complex flow control if one of them fails. are there other more compelling reasons for these async jobs?
...ANSWER
Answered 2020-Apr-10 at 03:01There are likely more reasons behind this design choice, but one is almost certainly use of Microservices. It is a popular technique, so demonstrating command of it is a good idea for answering design questions and benefits of it are well described on Wikipedia:
- Modularity: This makes the application easier to understand, develop, test, and become more resilient to architecture erosion.[6] This benefit is often argued in comparison to the complexity of monolithic architectures.[33]
- Scalability: Since microservices are implemented and deployed independently of each other, i.e. they run within independent processes, they can be monitored and scaled independently.[34]
- Integration of heterogeneous and legacy systems: microservices is considered as a viable mean for modernizing existing monolithic software application.[35][36] There are experience reports of several companies who have successfully replaced (parts of) their existing software by microservices, or are in the process of doing so.[37] The process for Software modernization of legacy applications is done using an incremental approach.[38]
- Distributed development: it parallelizes development by enabling small autonomous teams to develop, deploy and scale their respective services independently.[39] It also allows the architecture of an individual service to emerge through continuous refactoring.[40] Microservice-based architectures facilitate continuous integration, continuous delivery and deployment.[41] [42]
All of those apply in this case. Indeed, well-defined API makes the modules separate, reusable, easy to understand. Most likely each of the 3 modules will have very different execution time and CPU/memory requirements, so scaling them separately makes a lot of sense. Some companies like Amazon mentioned on the page might go much further splitting those modules into microservices based on the team number, so this split into 3 services can very well be chosen based on the assumption of having 3 teams, rather than technical constraints.
The page also describes criticism of the technique.
QUESTION
I'm reading about caching strategies such as cache-aside, write-through, write-back, ... In the specific cases of write-through and write-back, it is implied that the cache itself is responsible for writing to the database and the event queue, respectively (For full context, here is the article - https://github.com/donnemartin/system-design-primer#when-to-update-the-cache)
For example, write-through is illustrated as
Application code:
...ANSWER
Answered 2019-Jul-14 at 08:44It's part of the application. In fact, it would be more appropriate to call the example "data store code", instead of "cache code". The set_user method belongs to a base UserStore class, with different implementations based on data store type, write policy etc. For "write-through", it would be:
QUESTION
ARM offers emulators for development at Fixed Virtual Platforms (FVPs). ARM also announced ARMv8.4-a, which provides hardware acceleration for cryptographic algorithms, including SHA2-512, SHA3, SM3 and SM4. I have some C++ code I want t port to the new instructions.
I need access to a FVP or machine with ARMv8.4-a. I don't believe there is any silicon in the field with ARMv8.4-a at the moment. I think that means FVPs are my only choice at the moment.
My question is, do the FVP's support ARMv8.4?
...ANSWER
Answered 2018-Feb-11 at 03:55My question is, do the FVP's support ARMv8.4?
According to Barry Spotts of ARM FVP team:
Our ARM AEMv8 FVP is free and can be downloaded from https://developer.arm.com/products/system-design/fixed-virtual-platforms
It does support ARM 8.4 extensions. Linaro build does support our AEMv8 FVP.
It looks like QEMU added ARMv8.4-a support in February 2018 so the instructions can be emulated.
QUESTION
I am reading this article about a Twitter-like application. The type of storage where tweets, users, likes, etc. will be stored is a relational database. The database scheme is described here and drawn here.
As an Android developer, I coded my sample using SQLite. This is how I would code it:
...ANSWER
Answered 2017-Jan-22 at 19:32Shortly I placed an answer here, where the OP - like you in this question - was unsure about 1:n and n:m.
I assume, that your final sentence is the actual question you have:
Why do we need a many-to-many here? In my scheme I only use a one-to-many
The relation user-tweets is 1:n...
Think in objects
- user (id, name, ...)
- tweet (id, author (FK on user), datetime, content, ...)
The like is an object with sepecific details on its own:
- like (id, userid,tweetid,datetime,...)
For this you need a mapping table (you call it favourites)
There is a 1:n-relation from users to this mapping and a 1:n-relation from tweets to this mapping.
These two 1:n-relations form the m:n-relation together.
Now each tweet can be liked by many users and each user can like many tweets, but one user should (probably) not like the same tweet twice (unique key or even a two column PK?). And you might introduce a CHECK constraint to ensure, that the liking user and the author's userid is not the same (don't like your own tweets).
Is there anything wrong with my database scheme
You should never create constraints wihtout naming them
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Install system-design
You can use system-design like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the system-design component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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