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computer science whiteboard computer science whiteboard a blog about computer science and my personal experience in learning cs topics include but are limited to data structures and algorithms software engineering cloud computing data science database networking system design artificial intelligence and complexity tuesday february 21 2017 database concepts relational database a relational database is a digital database whose organization is based on the relational model of data as proposed by e f codd in 1970 the various software systems used to maintain relational databases are known as a relational database management system rdbms virtually all relational database systems use sql structured query language as the language for querying and maintaining the database relational model the relational model rm for database management is an approach to managing data using a structure and language consistent with first order predicate logic first described in 1969 by edgar f codd where all data is represented in terms of tuples grouped into relations a database organized in terms of the relational model is a relational database nosql a nosql originally referring to non sql non relational or not only sql database provides a mechanism for storage and retrieval of data which is modeled in means other than the tabular relations used in relational databases such databases have existed since the late 1960s but did not obtain the nosql moniker until a surge of popularity in the early twenty first century triggered by the needs of web 2 0 companies such as facebook google and amazon com nosql databases are increasingly used in big data and real time web applications nosql systems are also sometimes called not only sql to emphasize that they may support sql like query languages dimensional modeling dimensional modeling dm names a set of techniques and concepts used in data warehouse design it is considered to be different from entity relationship modeling er dimensional modeling does not necessarily involve a relational database the same modeling approach at the logical level can be used for any physical form such as multidimensional database or even flat files according to data warehousing consultant ralph kimball dm is a design technique for databases intended to support end user queries in a data warehouse it is oriented around understandability and performance according to him although transaction oriented er is very useful for the transaction capture it should be avoided for end user delivery data warehouse in computing a data warehouse dw or dwh also known as an enterprise data warehouse edw is a system used for reporting and data analysis and is considered a core component of business intelligence dws are central repositories of integrated data from one or more disparate sources they store current and historical data in one single place and are used for creating analytical reports for knowledge workers throughout the enterprise examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analysis olap and oltp online analytical processing olap is characterized by a relatively low volume of transactions queries are often very complex and involve aggregations for olap systems response time is an effectiveness measure olap applications are widely used by data mining techniques olap databases store aggregated historical data in multi dimensional schemas usually star schemas olap systems typically have data latency of a few hours as opposed to data marts where latency is expected to be closer to one day the olap approach is used to analyze multidimensional data from multiple sources and perspectives the three basic operations in olap are roll up consolidation drill down and slicing dicing 4 online transaction processing oltp is characterized by a large number of short on line transactions insert update delete oltp systems emphasize very fast query processing and maintaining data integrity in multi access environments for oltp systems effectiveness is measured by the number of transactions per second oltp databases contain detailed and current data the schema used to store transactional databases is the entity model usually 3nf 5 normalization is the norm for data modeling techniques in this system denormalization in computing denormalization is the process of trying to improve the read performance of a database at the expense of losing some write performance by adding redundant copies of data or by grouping data it is often motivated by performance or scalability in relational database software needing to carry out very large numbers of read operations data warehouse as an example performs some degree of denormalization examples of denormalization techniques include 1 materialised views which may implement the following a storing the count of the many objects in a one to many relationship as an attribute of the one relation b adding attributes to a relation from another relation with which it will be joined 2 star schemas which are also known as fact dimension models and have been extended to snowflake schemas 3 prebuilt summarisation or olap cubes normalization there are degrees of normalization you can apply to your database design in general vialiations of normal form will cause different types of anomalies anomalies a poorly designed database can cause anomalies in the data e g update delete insert anomaly constrains can prevent some anomalies minimal redundancy less possibility of anomalies functional dependency in relational database theory a functional dependency is a constraint between two sets of attributes in a relation from a database in other words functional dependency is a constraint that describes the relationship between attributes in a relation multivalued dependency in database theory a multivalued dependency is a full constraint between two sets of attributes in a relation in contrast to the functional dependency the multivalued dependency requires that certain tuples be present in a relation therefore a multivalued dependency is a special case of tuple generating dependency the multivalued dependency plays a role in the 4nf database normalization a multivalued dependency is a special case of a join dependency with only two sets of values involved i e it is a binary join dependency superkey a superkey is defined in the relational model of database organization as a set of attributes of a relation variable for which it holds that in all relations assigned to that variable there are no two distinct tuples rows that have the same values for the attributes in this set a super key can be defined as a set of attributes of a relation schema upon which all attributes of the schema are functionally dependent candidate key in the relational model of databases a candidate key of a relation is a minimal superkey for that relation that is a set of attributes such that 1 the relation does not have two distinct tuples e g rows or records in common database language with the same values for these attributes which means that the set of attributes is a superkey 2 there is no proper subset of these attributes for which 1 holds which means that the set is minimal first normal form 1 types values must be atomic e g actor id role 1 warrior beast 2 no repeating attributes fields second normal form 1 follow first normal form 2 non key fields depend on the key field e g no fields from another entity are wanted only fk is needed third normal form 1 follow second normal form 2 has no transitive dependencies no dependencies from one non key field to another boyce codd normal form 3 5nf slightly stronger than 3nf a relational schema r is in boyce codd normal form if and only if for every one of its dependencies x y at least one of the following conditions hold 1 x y is a trivial functional dependency y x 2 x is a super key for schema r fourth normal form a table is in 4nf if and only if for every one of its non trivial multivalued dependencies x y x is a superkey that is x is either a candidate key or a superset thereof fifth normal form a table is said to be in the 5nf if and only if every non trivial join dependency in it is implied by the candidate keys domain key normal form domain key normal form dk nf is a normal form used in database normalization which requires that the database contains no constraints other than domain constraints and key constraints a domain constraint specifies the permissible values for a given attribute while a key constraint specifies the attributes that uniquely identify a row in a given table the domain key normal form is achieved when every constraint on the relation is a logical consequence of the definition of keys and domains and enforcing key and domain restraints and conditions causes all constraints to be met thus it avoids all non temporal anomalies the reason to use domain key normal form is to avoid having general constraints in the database that are not clear domain or key constraints most databases can easily test domain and key constraints on attributes general constraints however would normally require special database programming in the form of stored procedures often of the trigger variety that are expensive to maintain and expensive for the database to execute therefore general constraints are split into domain and key constraints it s much easier to build a database in domain key normal form than it is to convert lesser databases which may contain numerous anomalies however successfully building a domain key normal form database remains a difficult task even for experienced database programmers thus while the domain key normal form eliminates the problems found in most databases it tends to be the most costly normal form to achieve posted by aaron zhao at 6 11 pm no comments email this blogthis share to x share to facebook share to pinterest sunday june 5 2016 housing price prediction using machine learning techniques this is an individual research paper i wrote during my college years for machine learning posted by aaron zhao at 7 41 pm no comments email this blogthis share to x share to facebook share to pinterest labels computer science housing price prediction machine learning prediction sunday may 29 2016 access aws linux instance over ssh how to access your aws linux instance over ssh there are two options 1 access with your pem key file which you obtained from aws when creating an instance 2 access with password before you will be able to ssh into your instance via option 2 you will have to set up the account and password via option 1 option 1 steps 1 log into your aws web portal and find your linux instance in the instances list 2 right click on the instance and click on the connect option 3 you will find your public dns address e g ec2 your instance us your region compute amazonaws com 4 find your pem key file path e g user doc my key file pem and do ssh in your client by ssh i user doc my key file pem ec2 user ec2 your instance us your region compute amazonaws com note ec2 user is the default user name for your linux instance if it happens to be different refer to this for details of how to obtain it if it asks you about rsa key fingerprint just type yes 5 if you have successfully logged into the instance over ssh after previous 4 steps you will now be able to set up password access over ssh to your instance so that you don t always need your pem key file option 2 set up password access 1 ssh i user doc my key file pem ec2 user ec2 your instance us your region compute amazonaws com 2 cd 3 sudo useradd s bin bash m d home username g root username 4 sudo passwd username enter new pwd retype new pwd 5 add the user as a sudoer optional sudo visudo and add the following line to the file username all all all all 6 enable password access sudo vi etc ssh sshd_config and change passwordauthentication from no to yes 7 restart ssh service by sudo etc init d ssh restart or sudo etc init d sshd restart 9 log out and log in using ssh username ec2 your instance us your region compute amazonaws com enter pwd posted by aaron zhao at 2 06 pm no comments email this blogthis share to x share to facebook share to pinterest labels aws linux ssh ssh password access thursday may 26 2016 trie what is a trie data structure if you know what a tree data structure is you can think of a trie as an ordered tree such that it is similar to a binary search tree but it it not necessary to have both key and value given a node of the tree the node has a value if and only if it has a valid key let s look at an example trie is especially powerful and commonly used when dealing with letters and words the above is a trie example from wikipedia that uses words as key and integer as value it takes string as an input and outputs an integer value if there is a match so trie_example get tea will return an integer 3 and trie_example get te will return null since there is no value associated with that node tea is considered a valid key while te is not since we define the key is valid if it is a valid english word this kind of trie can be very powerful in time complexity when dealing with words but it also uses a lot of space especially when there are lengthy words a space optimized trie called radix tree can be used to solve this problem use word matching as an example radix tree will not only store one letter in each node but as many as its children they share posted by aaron zhao at 8 07 pm no comments email this blogthis share to x share to facebook share to pinterest labels computer science data structure tree trie home subscribe to posts atom about me aaron zhao view my complete profile blog archive 2017 1 february 1 database concepts 2016 3 june 1 may 2 simple theme powered by blogger