on 07-Nov-2019 (Thu)

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In AWS, you use [...] if you want a fast in-memory database used to take load off of your main OLTP db for repeat queries.

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ElastiCache

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Теорема 4.2 (критерий Коши равномерной сходимости функционально- го ряда)

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[default - edit me]

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[default - edit me]

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Для того чтобы ∞ P k=1 u k (x) X ⇒ S(x), необходимо и достаточно, чтобы ∀ε > 0 ∃N = N(ε) (не зависящий от x ∈ X) такой, что ∀n > N, ∀p ∈ N и ∀x ∈ X выполнялось неравенство |S n+p (x) − S n (x)| = ¯ ¯ ¯ ¯ ¯ n+p X k=n+1 u k (x) ¯ ¯ ¯ ¯ ¯ < ε

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In AWS, for DynamoDB, the main building blocks are [...] , which contain Items, which are in turn made of Attributes

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Tables

^^^ e.g.:
"People" Table that has following "person" Item:
{
"PersonID": 101,
"LastName": "Smith",
"FirstName": "Fred",
"Phone": "555-1234"
}
The table is People, the Item is the person JSON above, and the attributes are the individual elements of the JSON (e.g. LastName, FirstName, etc)

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In AWS, for DynamoDB, the main building blocks are Tables, which contain [...]s, which are made of Attributes

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Items

^^^ e.g.:
"People" Table that has following "person" Item:
{
"PersonID": 101,
"LastName": "Smith",
"FirstName": "Fred",
"Phone": "555-1234"
}
The table is People, the Item is the person JSON above, and the attributes are the individual elements of the JSON (e.g. LastName, FirstName, etc)

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In AWS, for DynamoDB, the main building blocks are Tables, which contain Items, which are made of [...]s

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Attributes

^^^e.g.:
"People" Table that has following "person" Item:
{
"PersonID": 101,
"LastName": "Smith",
"FirstName": "Fred",
"Phone": "555-1234"
}
The table is People, the Item is the person JSON above, and the attributes are the individual elements of the JSON (e.g. LastName, FirstName, etc)

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In AWS, DynamoDB uses the [...] [...] 's value as input to an internal hash function whose output determines the physical storage block internal to DynamoDB in which the item will be stored.

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Partition Key

^^ e.g. In "Music" table, the Partition key is "Artist" and Sort key is "songName", both attributes together are the primary key (unique identifiers you can query on).

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In AWS, DynamoDB uses the partition key's value as input to an internal hash function whose output determines the physical storage block internal to DynamoDB in which the item will be stored. All items with the same partition key value are stored together, in order by the [...] [...] value.

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Sort Key

^^ e.g. In "Music" table, the Partition key is "Artist" and Sort key is "songName", both attributes together are the primary key (unique identifiers you can query on).

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In AWS, for DynamoDB, the primary key always has the [...] key and optionaly a Sort key.

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Partition

^^ e.g. In "Music" table, the Partition key is "Artist" and Sort key is "songName", both attributes together are the primary key (unique identifiers you can query on).

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In AWS, for DynamoDB, the primary key always has the Partition key and optionaly a [...] key.

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Sort

e.g. In "Music" table, the Partition key is "Artist" and Sort key is "songName", both attributes together are the primary key (unique identifiers you can query on).

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In AWS, for DynamoDB, you can only query on the prmiary key (Partition key or Parition key/sort key combo) unless you create additional [...] [...]

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Secondary Indexes

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In AWS, for DynamoDB, you get fast speed because data is stored on [...] storage

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SSD

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In AWS, for DynamoDB, you get your data spread across [...] geographically distinct data centres (AZs).

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3

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In AWS, for DynamoDB, by deafult you get [...] [...] Reads, which means when you write new data or update data, you will be able to read the updated data within about 1 second (anything earlier may not return the latest data update)

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Eventual Consistent

^^^ but stronly consistent Reads also available (but not by deafault), where as soon as you get 200 back from the write call, you can read right away the updated data.

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In AWS, Redshift is a super fast OLAP relational db solution because it stores and compresses data by [...]s (THINK WHY THIS IS GOOD/FAST)

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Columns

^^^ so it takes less space to store and also better compression algorithms can be used as columns have similar data

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In AWS, Redshift is a super fast OLAP relational db solution because it stores and compresses data by column and also because it employs [...acronym here...] , where there is a leader node that takes the queries from the client an distributes it to several compute nodes.

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MPP (Massive Parallel Processing)

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In AWS, Redshift is a super fast OLAP relational db solution because it stores and compresses data by column and also because it employs MPP (Massive Parrallel Processing), where there is a leader node that takes the queries from client an distributes it to several [...] nodes.

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Compute

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In AWS, Reshift is available in [...] AZ.

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1

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In AWS, Redshift can do automated backups where you can restore your data to within a second of between 0 to [...] retention days

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35

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In AWS, Redshift keeps [...] copies of your data (think where each copy is stored)

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3

Redshift keeps 3 copies of your data, the data on the compute node, as well as a replica on the compute node and a backup on S3

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In AWS, Redshift can support Disaster Recovery by asynchronosly replicating your snapshots to S3 in another [...]

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Region

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proposiciones

Tags

#Gödel

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formalmente

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indecidibles

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Principia Mathematica

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sistemas conexos

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In AWS, [...] is Amazon's own MySQL/PostgreSQL campatible RDS DB engine that combines the cost-effectiveness of open-source DB solutions with the reliability of commercial DBs

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Aurora

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In AWS, Aurora (Amazon's own DB) is a good option for your RDS engine, because it has very high availability and durability as it keeps at least [...] total copies of you data, [...] copies in at least [...] different Availablility Zones <--(A different number for each occulsion obviously)

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6 = 2 x 3

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In AWS, Aurora (Amazon's own DB) is a good option for your RDS engine because it supports 2 types of read replicas, MySQL replicas, and Aurora Replicas, which support [...] [...] (only Aurora replicas do, not MySQL)

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Automated Failovers

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In AWS, for RDS, when you choose Aurora, automated backups are turned on by default, but you can also take snapshots and share them with other [...] [...]

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AWS Accounts

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In AWS (and computing in general), if you have an E-commerce site and you want to show the user the top 10 most purchased items (which does not change all that often), instead of querying the info from the main OLTP DB (like RDS MySQL) each time, you would instead use your [...] [...] DB.

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In-memory Cache

^^ e.g. ElastiCache

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In AWS, for your ElastiCache engine, you would choose [...] , if you just want a simple/easy to use in-memory cache that is horizontally scalable (but you don't care about advanced features like multi AZ/complex data types/backup and restore/etc).

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Memcached

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In AWS, for your ElastiCache engine, you would choose [...] , if you have some advanced features you want like Multi-AZ, Backup and Restore, Persistence, Advanced data types, complex ranking/sorting.

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Redis

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In AWS, for your ElastiCache engine, you would choose Redis, if you have some advanced features you want like [...]-[...] , Backup and Restore, Persistence, Advanced data types, complex ranking/sorting.

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Multi-AZ

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In AWS, for your ElastiCache engine, you would choose Redis, if you have some advanced features you want like Multi-AZ, [...] and [...] , Persistence, Advanced data types, complex ranking/sorting.

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Backup and Restore