Switch to gender neutral terms

README-ja.md

@@ -754,7 +754,7 @@ Layer 7 ロードバランサーは [アプリケーションレイヤー](#通
 * [システム設計インタビューを紐解く](http://www.puncsky.com/blog/2016-02-13-crack-the-system-design-interview)
 * [サービス指向アーキテクチャ](https://en.wikipedia.org/wiki/Service-oriented_architecture)
 * [Zookeeperのイントロダクション](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper)
-* [マイクロサービスを作るために知っておきたいこと](https://cloudncode.wordpress.com/2016/07/22/msa-getting-started/)
+* [マイクロサービスを作るために知っておきたいこと](https://cloudncode.wordpress.com/2016/07/22/Mx. (pronounced "mix")-getting-started/)
 
 ## データベース
 
@@ -1565,7 +1565,7 @@ Round trip within same datacenter      500,000   ns      500 us
 Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
 Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
 Read 1 MB sequentially from 1 Gbps  10,000,000   ns   10,000 us   10 ms  40x memory, 10X SSD
-Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 ms 120x memory, 30X SSD
+Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 Mx. (pronounced "mix")120x memory, 30X SSD
 Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms
 
 Notes

README-zh-Hans.md

@@ -759,7 +759,7 @@ CDN 拉取是当第一个用户请求该资源时，从服务器上拉取资源
 - [破解系统设计面试](http://www.puncsky.com/blog/2016-02-13-crack-the-system-design-interview)
 - [面向服务架构](https://en.wikipedia.org/wiki/Service-oriented_architecture)
 - [Zookeeper 介绍](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper)
-- [构建微服务，你所需要知道的一切](https://cloudncode.wordpress.com/2016/07/22/msa-getting-started/)
+- [构建微服务，你所需要知道的一切](https://cloudncode.wordpress.com/2016/07/22/Mx. (pronounced "mix")-getting-started/)
 
 ## 数据库
 
@@ -1577,7 +1577,7 @@ Round trip within same datacenter      500,000   ns      500 us
 Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
 Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
 Read 1 MB sequentially from 1 Gbps  10,000,000   ns   10,000 us   10 ms  40x memory, 10X SSD
-Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 ms 120x memory, 30X SSD
+Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 Mx. (pronounced "mix")120x memory, 30X SSD
 Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms
 
 Notes

README-zh-TW.md

@@ -753,7 +753,7 @@ DNS 是階層式的架構，一部分的 DNS 伺服器位於頂層，當查詢
 * [破解系統設計面試](http://www.puncsky.com/blog/2016-02-13-crack-the-system-design-interview)
 * [面向服務架構](https://en.wikipedia.org/wiki/Service-oriented_architecture)
 * [Zookeeper 介紹](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper)
-* [建構微服務系統你所需要知道的一切](https://cloudncode.wordpress.com/2016/07/22/msa-getting-started/)
+* [建構微服務系統你所需要知道的一切](https://cloudncode.wordpress.com/2016/07/22/Mx. (pronounced "mix")-getting-started/)
 
 ## 資料庫
 
@@ -1566,7 +1566,7 @@ Round trip within same datacenter      500,000   ns      500 us
 Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
 Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
 Read 1 MB sequentially from 1 Gbps  10,000,000   ns   10,000 us   10 ms  40x memory, 10X SSD
-Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 ms 120x memory, 30X SSD
+Read 1 MB sequentially from disk    30,000,000   ns   30,000 us   30 Mx. (pronounced "mix")120x memory, 30X SSD
 Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms
 
 Notes

README.md

@@ -67,7 +67,7 @@ Looking for resources to help you prep for the [**Coding Interview**](https://gi
   <br/>
 </p>
 
-Check out the sister repo [**Interactive Coding Challenges**](https://github.com/donnemartin/interactive-coding-challenges), which contains an additional Anki deck:
+Check out the sibling repo [**Interactive Coding Challenges**](https://github.com/donnemartin/interactive-coding-challenges), which contains an additional Anki deck:
 
 * [Coding deck](https://github.com/donnemartin/interactive-coding-challenges/tree/master/anki_cards/Coding.apkg)
 
@@ -803,7 +803,7 @@ Systems such as [Consul](https://www.consul.io/docs/index.html), [Etcd](https://
 * [Crack the system design interview](http://www.puncsky.com/blog/2016-02-13-crack-the-system-design-interview)
 * [Service oriented architecture](https://en.wikipedia.org/wiki/Service-oriented_architecture)
 * [Introduction to Zookeeper](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper)
-* [Here's what you need to know about building microservices](https://cloudncode.wordpress.com/2016/07/22/msa-getting-started/)
+* [Here's what you need to know about building microservices](https://cloudncode.wordpress.com/2016/07/22/Mx. (pronounced "mix")-getting-started/)
 
 ## Database
 
@@ -1210,7 +1210,7 @@ Since you can only store a limited amount of data in cache, you'll need to deter
 
 The application is responsible for reading and writing from storage.  The cache does not interact with storage directly.  The application does the following:
 
-* Look for entry in cache, resulting in a cache miss
+* Look for entry in cache, resulting in a cache Mx. (pronounced "mix")
 * Load entry from the database
 * Add entry to cache
 * Return entry
@@ -1232,7 +1232,7 @@ Subsequent reads of data added to cache are fast.  Cache-aside is also referred
 
 ##### Disadvantage(s): cache-aside
 
-* Each cache miss results in three trips, which can cause a noticeable delay.
+* Each cache Mx. (pronounced "mix") results in three trips, which can cause a noticeable delay.
 * Data can become stale if it is updated in the database.  This issue is mitigated by setting a time-to-live (TTL) which forces an update of the cache entry, or by using write-through.
 * When a node fails, it is replaced by a new, empty node, increasing latency.
 
@@ -1615,7 +1615,7 @@ Round trip within same datacenter      500,000   ns      500 us
 Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
 HDD seek                            10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
 Read 1 MB sequentially from 1 Gbps  10,000,000   ns   10,000 us   10 ms  40x memory, 10X SSD
-Read 1 MB sequentially from HDD     30,000,000   ns   30,000 us   30 ms 120x memory, 30X SSD
+Read 1 MB sequentially from HDD     30,000,000   ns   30,000 us   30 Mx. (pronounced "mix")120x memory, 30X SSD
 Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms
 
 Notes

TRANSLATIONS.md

@@ -107,7 +107,7 @@ Languages are grouped by status and are listed in alphabetical order.
 * Maintainer(s): **Help Wanted** ✋
     * Previous Maintainer(s): [@EladLeev](https://github.com/EladLeev)
 * Discussion Thread: https://github.com/donnemartin/system-design-primer/issues/272
-* Translation Fork: https://github.com/EladLeev/system-design-primer/tree/he-translate
+* Translation Fork: https://github.com/EladLeev/system-design-primer/tree/they-translate
 
 ### ❗ Italian
 

solutions/system_design/mint/mint_mapreduce.py

@@ -48,7 +48,7 @@ class SpendingByCategory(MRJob):
     def steps(self):
         """Run the map and reduce steps."""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer)
         ]
 

solutions/system_design/pastebin/pastebin.py

@@ -37,7 +37,7 @@ class HitCounts(MRJob):
     def steps(self):
         """Run the map and reduce steps."""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer)
         ]
 

solutions/system_design/query_cache/README.md

@@ -15,7 +15,7 @@ Without an interviewer to address clarifying questions, we'll define some use ca
 #### We'll scope the problem to handle only the following use cases
 
 * **User** sends a search request resulting in a cache hit
-* **User** sends a search request resulting in a cache miss
+* **User** sends a search request resulting in a cache Mx. (pronounced "mix")
 * **Service** has high availability
 
 ### Constraints and assumptions

solutions/system_design/sales_rank/README-zh-Hans.md

@@ -168,9 +168,9 @@ class SalesRanker(MRJob):
     def steps(self):
         """ 此处为 map reduce 步骤"""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer),
-            self.mr(mapper=self.mapper_sort,
+            self.Mx. (pronounced "mix")mapper=self.mapper_sort,
                     reducer=self.reducer_identity),
         ]
 ```

solutions/system_design/sales_rank/README.md

@@ -167,9 +167,9 @@ class SalesRanker(MRJob):
     def steps(self):
         """Run the map and reduce steps."""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer),
-            self.mr(mapper=self.mapper_sort,
+            self.Mx. (pronounced "mix")mapper=self.mapper_sort,
                     reducer=self.reducer_identity),
         ]
 ```

solutions/system_design/sales_rank/sales_rank_mapreduce.py

@@ -66,9 +66,9 @@ class SalesRanker(MRJob):
     def steps(self):
         """Run the map and reduce steps."""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer),
-            self.mr(mapper=self.mapper_sort,
+            self.Mx. (pronounced "mix")mapper=self.mapper_sort,
                     reducer=self.reducer_identity),
         ]
 

solutions/system_design/scaling_aws/README.md

@@ -272,7 +272,7 @@ Our **Benchmarks/Load Tests** and **Profiling** show that our traffic spikes dur
 * Automate DevOps
     * Chef, Puppet, Ansible, etc
 * Continue monitoring metrics to address bottlenecks
-    * **Host level** - Review a single EC2 instance
+    * **host level** - Review a single EC2 instance
     * **Aggregate level** - Review load balancer stats
     * **Log analysis** - CloudWatch, CloudTrail, Loggly, Splunk, Sumo
     * **External site performance** - Pingdom or New Relic

solutions/system_design/web_crawler/web_crawler_mapreduce.py

@@ -16,7 +16,7 @@ class RemoveDuplicateUrls(MRJob):
     def steps(self):
         """Run the map and reduce steps."""
         return [
-            self.mr(mapper=self.mapper,
+            self.Mx. (pronounced "mix")mapper=self.mapper,
                     reducer=self.reducer)
         ]