B4M36DS2, BE4M36DS2: Database Systems 2
Basic Information
- Annotations:
B4M36DS2 (Czech),
BE4M36DS2 (English)
- Lecturer and tutor: Martin Svoboda
- Schedule: B4M36DS2, BE4M36DS2
- Lectures: Monday 9:15 - 10:45 (KN:E-301) (English)
- Practical classes (group 101): Monday 12:45 - 14:15 (KN:E-328) (Czech)
- Practical classes (group 102): Monday 14:30 - 16:00 (KN:E-328) (English)
- Practical classes (group 103): Monday 16:15 - 17:45 (KN:E-328) (Czech)
- Table with points from practical classes, homework assignments and exam tests
Exam Dates
- Wednesday 15. 1. 2020: 9:30 - 11:45 (KN:E-301)
- Wednesday 22. 1. 2020: 9:30 - 11:45 (KN:E-301)
- Wednesday 29. 1. 2020: 10:00 - 12:15 (KN:E-301)
- Wednesday 5. 2. 2020: 9:30 - 11:45 (KN:E-301)
- Wednesday 12. 2. 2020: 9:30 - 11:45 (KN:E-301)
- There will be one exam date during the summer examination period
- There will be no additional exam dates
Homework Deadlines
- 00 - Topic selection: Monday 14. 10. 2019 until 23:59
- 01 - XQuery: Sunday 20. 10. 2019 until 23:59 (delays are not penalized)
- 02 - SPARQL: Sunday 27. 10. 2019 until 23:59 (delays are not penalized)
- 03 - MapReduce: Sunday 10. 11. 2019 until 23:59
- 04 - Redis: Sunday 17. 11. 2019 until 23:59
- 05 - Riak: Sunday 24. 11. 2019 until 23:59
- 06 - Cassandra: Sunday 1. 12. 2019 until 23:59
- 07 - MongoDB: Sunday 15. 12. 2019 until 23:59
- 08 - Neo4j: Friday 3. 1. 2020 until 23:59
Lectures
- 23. 09. 2019: 01 - Introduction: Big Data, NoSQL Databases
- 30. 09. 2019: 02 - Data Formats: XML, JSON, BSON, RDF, Protocol Buffers
- 07. 10. 2019: 03 - XML Databases: XPath, XQuery
- 14. 10. 2019: 04 - RDF Stores: SPARQL
- 21. 10. 2019: 05 - Apache Hadoop: MapReduce, HDFS
- 04. 11. 2019: Canceled
- 11. 11. 2019: 06 - Basic Principles: Scaling, Sharding, Replication, CAP Theorem, Consistency
- 18. 11. 2019: 07 - Key-Value Stores: RiakKV
- 25. 11. 2019: 08 - Wide Column Stores: Cassandra, CQL
- 02. 12. 2019: 09 - Document Databases: MongoDB
- 09. 12. 2019: 10 - Graph Databases: Neo4j, Cypher
- 16. 12. 2019: 11 - Advanced Aspects: Graph Databases
- 06. 01. 2020: 12 - Advanced Aspects: Transactions, Performance Tuning, Visualization
Practical Classes
Formal Requirements
- Attendance during lectures as well as practical classes is not compulsory, yet warmly recommended
- Altogether 8 individual homework assignments will take place during the semester
- Everyone must choose their distinct topic, not later than at the third practical class
- This topic must be reported to and explicitly accepted by the lecturer in advance
- Possible topics could be: library, cinema, cookbook, university, flights, etc.
- See the list below for additional suitable topics, feel free to choose your own topic
- Your homework solutions must be within the topic, original, realistic, and non-trivial
- Solutions can only be submitted via a script executed on the corresponding server
- At most 140 points in total can be gained for all the homework assignments
- Solutions are awarded by up to 20, 15 or 10 points respectively, depending on the assignment
- In case of any shortcomings, fewer points will be awarded appropriately
- Solutions can be submitted even repeatedly, only the latest version is assessed
- Once a given assignment is assessed by the lecturer, it cannot be resubmitted once again
- Delay of one whole day is penalized by 5 points, shorter delays are penalized proportionally
- Should the delay be even longer, the penalty stays the same and does not further increase
- All the homework assignments must be submitted before the intended exam date in order to be considered
- None of the homework assignments is compulsory, yet you are encouraged to submit all of them
- During some of the practical classes, extra activity points can be acquired, too
- At least 120 points is required for the course credit to be granted
- Half of all the points above this boundary is transferred as bonus points to the exam
- Only students with a course credit already acquired can sign up for the final exam
- The final exam consists of a compulsory written test and an optional oral examination
- At most 100 points can be acquired from the actual final written test
- This test consists of a theoretical part (open and multiple choice questions) and a practical part (exercises)
- Having less than 30% points from any of the two parts prevents from passing the exam successfully
- The final score corresponds to the sum of the written test and bonus points, if any
- Based on the result, everyone can voluntarily choose to undergo an oral examination
- In such a case, the final score is further adjusted by up to minus 10 to plus 5 points
- Final grade: 90 points and more for A, 80+ for B, 70+ for C, 60+ for D, and 50+ for E
Homework Assignments
- Preliminaries:
- NoSQL server: nosql.ms.mff.cuni.cz:42222
- Login and password: sent by e-mail
- Tools:
- Submissions:
- Use sftp or WinSCP tools to upload your submission files to the NoSQL server
- Put these files into a directory ~/assignments/name/, where name is a name of a given homework
- I.e. xquery, sparql, mapreduce, riak, redis, cassandra, mongodb, neo4j (case sensitive)
- Use ssh or PuTTY tools to open a remote shell connection to the NoSQL server
- Based on the instructions provided for a given homework assignment, verify that everything is working as expected
- Go to the ~/assignments/ directory and execute submit name, where name is once again the name of the homework
- Wait for the confirmation of success, otherwise your homework is not considered to be submitted
- Should any complications appear, send your solution by e-mail to martin.svoboda@fel.cvut.cz
- Just for your convenience, you can check the submitted files in the ~/submissions/ directory
- Requirements:
- Respect the prescribed names of individual files to be submitted (case sensitive)
- Place all the files in the root directory of your submission
- Do not include shared libraries or files that are not requested
- I.e. do not submit files that were not explicitly requested
- Do not redirect or suppress both standard and error outputs in your shell scripts
- All your files must be syntactically correct and executable without errors
1: XQuery
- Points: 20
- Assignment:
- Create an XML document with sample data from the domain of your individual topic
- Work with mutually interlinked entities of at least 3 different types (e.g. lines, flights and tickets)
- Insert data about at least 15 particular entities (e.g. 3 lines, 4 flights, 8 tickets)
- Create expressions for exactly 2 different XPath queries (i.e. not more, not less)
- Use each of the following constructs at least once
- Axes: descendant or descendant-or-self or // abbreviation
- Predicates (all of the following): path expression (existence test), position testing, value comparison, general comparison
- Create expressions for exactly 3 different XQuery queries (that cannot be expressed solely using XPath)
- Use each of the following constructs at least once
- Direct or computed constructor
- FLWOR expression (with at least one FOR clause)
- Conditional expression
- Existential or universal quantifier
- Requirements:
- Both XML document and queries must be well-formed (i.e. syntactically correct)
- Put each XPath / XQuery expression into a standalone file (e.g. xpath1.xp)
- Always add a comment describing the intended query meaning in natural language via (: comment :)
- Each query expression must be evaluated to a non-empty sequence
- Submission:
- data.xml: XML document with your data to be queried
- xpath1.xp and xpath2.xp: files with XPath expressions
- xquery1.xq, xquery2.xq, and xquery3.xq: files with XQuery expressions
- Execution:
- Execute the following shell command to evaluate each individual XPath or XQuery query expression
- saxonb-xquery -s $DataFile $QueryFile
- $DataFile is the input XML document to be queried, i.e. data.xml
- $QueryFile is a file with query expression to be evaluated, e.g. xquery1.xq
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 20. 10. 2019 until 23:59 (delays are not penalized)
2: SPARQL
- Points: 20
- Assignment:
- Create a TTL document with sample RDF triples within your individual topic
- Use the Turtle notation in particular
- Work with mutually interlinked resources of at least 3 different types (e.g. lines, flights and tickets)
- Insert data about at least 15 particular resources (e.g. 3 lines, 4 flights, 8 tickets)
- Use each of the following constructs at least once
- Object list or predicate-object list
- Blank nodes (either using _ prefix or brackets [])
- Create expressions for exactly 5 different SPARQL queries (SELECT query form in particular)
- Use each of the following constructs at least once
- Basic graph pattern
- Group graph pattern
- Optional graph pattern (OPTIONAL)
- Alternative graph pattern (UNION)
- Difference graph pattern (MINUS)
- FILTER constraint
- Aggregation (GROUP BY with or without HAVING clause)
- Sorting (ORDER BY clause)
- Requirements:
- Both TTL document and queries must be well-formed (i.e. syntactically correct)
- Put each SPARQL query expression into a standalone file (e.g. query1.sparql)
- Always add a comment describing the intended query meaning in natural language via # comment
- Each query expression must be evaluated to a non-empty solution sequence
- Both the data file a query files must contain declarations of all prefixes used, including rdf: and similar
- Use @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . in your data file
- Use PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> in your query file
- Do not use FROM clauses in your queries, the input data file will automatically be accessible as the default graph
- Submission:
- data.ttl: TTL document with your RDF data to be queried
- query1.sparql, ..., query5.sparql: files with SPARQL query expressions
- Execution:
- Execute the following shell command to evaluate each individual SPARQL query expression
- sparql --data $DataFile --query $QueryFile
- $DataFile is the input RDF document to be queried, i.e. data.ttl
- $QueryFile is a file with query expression to be evaluated, e.g. query1.sparql
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 27. 10. 2019 until 23:59 (delays are not penalized)
3: MapReduce
- Points: 20
- Assignment:
- Create an input text file with sample data from the domain of your individual topic
- Insert realistic and non-trivial data about at least 10 entities of one type
- Put each of these entities on a separate line, i.e. assume that each line of the input file yields one input record
- Organize the actual entity attributes in whatever way you are able to easily parse
- E.g. Medvídek 2007 53 100 Trojan Macháček Vilhelmová corresponding to a pattern Movie Year Rating Length Actors...
- Implement a non-trivial MapReduce job
- Choose from aggregation, grouping, filtering or any other general MapReduce usage pattern
- Use WordCount.java source file as a basis for your own implementation
- Both the Map and Reduce functions should be non-trivial, each about 10 lines of code
- It is not necessary to implement the Combine function
- Comment the source file and also provide a description of the problem you are solving
- You may also create a shell script that allows for the execution of your entire MapReduce job
- I.e. compile source files, deploy input file, execute the actual job, retrieve its result, ...
- However, this script is not supposed to be submitted and serves just for your own convenience
- Even if you do so, it will not be used for the purpose of homework assessment in any way
- Requirements:
- You may split your MapReduce job implementation into multiple Java source files
- They all must be located in the submission root directory
- At least MapReduce.java source file with its public MapReduce class is required
- This class is expected to represent the main class of the entire MapReduce job
- Do not change the way how command line arguments are processed
- I.e. the only two arguments represent the input and output HDFS locations respectively
- Do not use packages in order to organize your Java source files
- Assume that only hadoop-common-3.1.1.jar and hadoop-mapreduce-client-core-3.1.1.jar libraries will be linked with your project
- Do not submit your Netbeans (or any other) project directory, do not submit Hadoop (or any other) libraries
- Use Java Standard Edition version 7 or newer
- You are free to use your /user/f191_login/ HDFS home directory for debugging
- Homework assessment will take place in a different dedicated HDFS directory
- Submission:
- readme.txt: description of the input data structure and objective of the MapReduce job
- input.txt: text file with your sample input data (i.e. only one input file is permitted)
- MapReduce.java and possibly additional *.java: Java source files with your MapReduce implementation
- output.txt: expected output of your MapReduce job (i.e. submit the result of the execution you performed by yourself)
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 10. 11. 2019 until 23:59
4: Redis
- Points: 10
- Assignment:
- Create a script (ordinary text file) with a sequence of commands working with Redis
- Illustrate you can work with all data types (strings, lists, sets, sorted sets and hashes)
- In particular, perform all the following operations:
- Strings: 5 insertions (SET), 1 read (GET), 1 update (APPEND, SETRANGE, INCR, ...), 1 removal (DEL).
- Lists: 5 insertions (LPUSH, RPUSH, ...), 2 different reads (LPOP, RPOP, LINDEX, LRANGE), 1 removal (LREM).
- Sets: 5 insertions (SADD), 2 different reads (SISMEMBER, SUNION, SINTER, SDIFF), 1 removal (SREM).
- Sorted sets: 5 insertions (ZADD), 1 read (ZRANGE, ZRANGEBYSCORE), 1 update (ZINCRBY), 1 removal (ZREM).
- Hashes: 5 insertions (HSET, HMSET), 2 different reads (HGET, HMGET, HKEYS, HVALS, ...), 1 removal (HDEL).
- Your database (i.e. keys and values) as well as commands must be realistic and within your individual topic
- E.g. use a hash to store a mapping from seats to passengers for each flight
- HMSET seat-map-EK140-20171121 42A Peter 65F John
- Key seat-map-EK140-20171121 is composed from a fixed prefix (seat-map), flight number (EK140) and date of departure (20171121)
- The actual mapping contains pairs of seat numbers and passenger names, e.g. 42A Peter
- Add comments to your script using the ECHO command
- Describe at least the intended structure of your keys and values in natural language
- Requirements:
- Only use the database you are supposed to use when working on the assignment
- Your database number was sent to you by e-mail at the beginning of the semester
- Do not switch to your database when you are inside your script
- I.e. do not use a SELECT command to change the active database from within the script
- Specify the intended database number outside your script using command line options (see below)
- Note that a different dedicated database will be used when assessing your homework
- You can assume that this database will be completely empty at the beginning
- Submission:
- script.txt: text file with Redis database commands
- Execution:
- Execute the following shell command to evaluate the whole REDIS script
- cat $ScriptFile | redis-cli -n $DatabaseNumber
- $ScriptFile is a file with REDIS commands to be executed, i.e. script.txt
- $DatabaseNumber is a number of database to be used, e.g. 5
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 17. 11. 2019 until 23:59
5: Riak
- Points: 15
- Assignment:
- Create a shell script that works with Riak database via its HTTP interface using the cURL tool
- Insert about 5 key-value objects of different entity types into each of 3 buckets
- You can work with any data format you like (e.g. text, JSON)
- However, always include content headers
- Include at least 5 meaningful links of at least 2 different tags
- Use a separate Link header for each individual link you want to define
- I.e., do not incorporate multiple links into a single Link header
- Execute 1 read and 1 update request
- Perform 2 link walking queries
- One with at least 1 navigational step
- Another with at least 2 navigational steps
- Remove all your objects at the end of your script (i.e. empty all your buckets)
- Requirements:
- Assume the following convention for names of your buckets: f191_login_bucket
- Replace login with your actual login name and bucket with the intended bucket name
- E.g. f191_svobom25_movies for a bucket of movies
- However, use the following convention when referencing your buckets in URLs: $1_bucket
- $1 is a script argument provided from outside of your script (see below)
- Its value will correspond to a prefix f191_login with login as your actual login name
- I.e., do not access your buckets directly so that this prefix can easily be changed
- Explain the real-world meaning of your link walking queries (# comment)
- Make sure your shell script is executable at all (i.e. has the x permission assigned)
- Also make sure your script can be executed repeatedly without failures
- Submission:
- script.sh: Bash script allowing to execute all the HTTP requests
- Execution:
- Execute the following shell command to evaluate the whole RIAK script
- ./script.sh $BucketPrefix
- $BucketPrefix is a prefix for names of your buckets, i.e. f191_login
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 24. 11. 2019 until 23:59
6: Cassandra
- Points: 15
- Assignment:
- Create a script (ordinary text file) with a sequence of CQL statements working with Cassandra database
- Define a schema for 2 tables for entities of different types
- Define at least one column for each of the following data types: tuple, list, set and map
- Insert about 5 rows into each of your tables
- Express at least 3 update statements
- You must perform replace, add and remove primitive operations (all of them) on columns of all collection types (all of them)
- I.e. you must involve at least altogether 9 different primitive operations on such columns
- Express 3 select statements
- Use WHERE and ORDER BY clauses at least once (both of them)
- Use ALLOW FILTERING in a query that cannot be evaluated without this instruction
- Create at least 1 secondary index
- Requirements:
- Only use your own keyspace when working on the assignment
- Name of this keyspace must be identical to your login name (f191_login)
- Do not create this keyspace in your script (assume it already exists)
- Do not switch to your keyspace when you are inside your script
- I.e. do not execute a USE command to change the active keyspace from within the script
- Specify the intended keyspace outside your script using command line options (see below)
- Note that a different dedicated keyspace will be used when assessing your homework
- You can assume that this keyspace will be completely empty at the beginning
- Submission:
- script.cql: text file with CQL statements
- Execution:
- Execute the following shell command to evaluate the whole CQL script
- cqlsh -k $KeyspaceName -f $ScriptFile
- $KeyspaceName is a name of keyspace that should be used (must already exist), e.g. f191_login
- $ScriptFile is a file with CQL queries to be executed, i.e. script.cql
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 1. 12. 2019 until 23:59
7: MongoDB
- Points: 20
- Assignment:
- Create a JavaScript script with a sequence of commands working with MongoDB database
- Explicitly create 2 collections for entities of different types
- I.e., create them using createCollection method
- Insert about 5 documents into each one of them
- These documents must be realistic, non-trivial, and with both embedded objects and arrays
- Interlink the documents using references
- Use both insert and save operations, each at least once
- Express 3 update operations (do not use save operation for this purpose)
- One without update operators
- One with at least 2 different update operators
- One based on the upsert mode
- Express 5 find queries (with non-trivial selections)
- Use at least one logical operator ($and, $or, $not)
- Use $elemMatch operator on array fields at least once
- Use both positive and negative projection (each at least once)
- Use sort modifier
- Describe the real-world meaning of all your queries in comments
- Express 1 MapReduce query (non-trivial, i.e. not easily expressed using ordinary find operation)
- Describe its meaning, contents of intermediate key-value pairs and the final output
- Note that reduce function must be associative, commutative, and idempotent
- Requirements:
- Call export LC_ALL=C in case you have difficulties in launching the mongo shell
- Only use your own database when working on the assignment
- Name of this database must be identical to your login name (f191_login)
- Do not switch to your database when you are inside your script
- I.e. do not execute USE database and nor db.getSiblingDB('database') commands
- Specify the intended database outside your script using command line options (see below)
- Note that a different dedicated database will be used when assessing your homework
- You can assume that this database will be completely empty at the beginning
- Print the output of your queries (find operations)
- Use db.collection.find().forEach(printjson); approach for this purpose
- Print the output of your MapReduce job using out: { inline: 1 } option
- I.e. do not redirect the output into a standalone collection
- Submission:
- script.js: JavaScript script with MongoDB database commands
- Execution:
- Execute the following shell command to evaluate the whole MongoDB script
- mongo $DatabaseName $ScriptFile
- $DatabaseName is a name of database that should be used, e.g. f191_login
- $ScriptFile is a file with MongoDB queries to be executed, i.e. script.js
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Sunday 15. 12. 2019 until 23:59
8: Neo4j
- Points: 20
- Assignment:
- Insert realistic nodes and relationships into your embedded Neo4j database
- Use a single CREATE statement for this purpose
- Insert altogether at least 10 nodes for entities of at least 2 different types (i.e. different labels)
- Insert altogether at least 15 relationships of at least 2 different types
- Include properties (both for nodes and relationships)
- Associate all your nodes with user-defined identifiers
- Express 5 Cypher query expressions
- Use at least once MATCH, OPTIONAL MATCH, RETURN, WITH, WHERE, and ORDER BY (sub)clauses (all of them)
- Aggregation in at least one query
- Requirements:
- Describe the meaning of your Cypher expressions in natural language (via // comment)
- Submission:
- queries.cypher: text file with a sequence of Cypher statements (including CREATE)
- Execution:
- Execute the following shell command to evaluate the whole Neo4j script
- cat $ScriptFile | neo4j-shell --path $DatabasePath --non-interactive
- $DatabasePath is a path to a directory that should contain / already contains Neo4j embedded database to be used, e.g. /home/f191_login/MyNeo4jDatabase
- $ScriptFile is a file with Cypher queries to be executed, i.e. queries.cypher
- Tools:
- References:
- Server: nosql.ms.mff.cuni.cz:42222
- Do not forget to execute the homework submission script!
- Deadline: Friday 3. 1. 2020 until 23:59
Individual Topics
- Try to propose your own original topic in the first place
- You can also get inspired by the following topics (in alphabetical order, in English and in Czech)
-
Access system,
Accommodation booking,
Accommodation comparator,
Accommodation sharing,
Agricultural production,
Air rescue service,
Air traffic management,
Airline,
Airport,
Armory,
Army,
Artworks,
Assignment submission,
ATM network,
Attendance system,
Auction,
Bakery,
Bank,
Bank account,
Bazaar,
Beekeeper,
Betting shop,
Beverages store,
Bike sharing,
Blog,
Boat rental,
Bookstore,
Botanic garden,
Brewery,
Bus station,
Bus tickets,
Business register,
Cadastre,
Cafe,
Canteens,
Car rental,
Car repair shop,
Casino,
Castles,
Catering,
Caves,
Cemetery,
Cinema,
City tours,
Classbook,
Collection and disposal of waste,
Collection of laws,
College dorm,
Computer games,
Conference,
Construction management,
Content management system,
Contract register,
Cookbook,
Cooking classes,
Council meetings,
Countries of the world,
Courier service,
Cowshed,
Dance school,
Deliveries,
Desk games,
Discussion forum,
Doctor's office,
Dog park,
Dog shelter,
Driving school,
Drugs,
Dump,
Educational institution,
Elections,
Electronic prescriptions,
Employee records,
Entertainment center,
Environmental center,
Exhibition,
Exhibition grounds,
Experience donation,
Fairy tales,
Farmer markets,
Finance manager,
Financial advisory,
Financial markets,
Fire protection,
Fishing equipment,
Fitness center,
Fleet,
Flight ticket booking,
Food bank,
Food distribution,
Football league,
Football team,
Forest kindergarten,
Foster care,
Gallery,
Gardening colony,
Gas station,
Glassworks,
Golf clubs,
Grant agency,
Grid,
Hair salon,
Handyman,
Hardware,
Health insurance,
High school,
Highway fees,
Hiking trails,
Hobby market,
Hockey league,
Holiday offers,
Horse racing,
Hospital,
Hotel,
Chamber of deputies,
Chess database,
Incinerator,
Industrial zone,
Insurance company,
Intelligence service,
Intersport arena,
Job offers,
Jurassic park,
Kindergarten,
Laboratory,
Labour office,
Language school,
Lego,
Leisure activities,
Library,
Log book,
Logistics center,
Logistics company,
Logistics warehouse,
Lottery,
Luggage storage,
Manufacturing processes,
Maternity hospital,
Medical reimbursement,
Meeting scheduling,
Menu,
Metro operation,
Military area,
Mobile operator,
Mobile phones,
Model trains,
Morgue,
Mountain rescue service,
Movies,
Multinational company,
Multiplex network,
Museum,
Music festival,
Music production,
Musical instruments,
National parks,
Nature reserve,
Newspaper publishing,
Non-bank loans,
Nuclear power plant,
Nutritional values,
Online exercises,
Online streaming service,
Orienteering,
Parking lot,
Parts catalog,
Patient medical card,
Pawnshop,
Payment cards,
Personal documents,
Personal trainer,
Pharmacy,
Photo album,
Pizzeria,
Plagiarism detection,
Planning calendar,
Police database,
Political parties,
Popular music,
Population register,
Post,
Postal addresses,
Poultry farming,
Prison,
Procurement,
Project management,
Property administration,
Psychiatric hospital,
Public greenery,
Public transport,
Railway network,
Real estate agency,
Recruitment agency,
Refugee camp,
Regulatory fees,
Research projects,
Research publications,
Restaurant,
Restaurant reservations,
Road closures,
Room reservation,
Scout group,
Scrapyard,
Security agency,
Seizures,
Shared travel,
Shooting range,
Shopping center,
Ski school,
Skiing area,
Social benefits,
Social network,
Software development,
Spare parts,
Sports club,
Sports tournament,
Stable,
Statement of work,
Stock exchange,
Student book,
Study abroad,
Study materials,
Study system,
Subsidy programs,
Summer camp,
Supermarket,
Sweet-shop,
Swimming pool,
Symphony orchestra,
Tax office,
Taxi service,
Teahouse,
Theater,
Theater plays,
Time tables,
Tollgates,
Tourism,
Tourist group,
Traffic accidents,
Traffic control center,
Train station,
Transport company,
Transport control,
Travel agency,
Trial,
Truck transport,
TV program,
TV series,
Universe,
Vaccination abroad,
Veterinary clinic,
Video shop,
Virtual tours,
Visas,
War conflicts,
Water park,
Water supply,
Weapons,
Weather forecast,
Webhosting,
Webshop,
Wedding dress rental,
Wholesale,
Winter road cleaning,
World heritage list,
Zoning plan,
Zoo
-
Adresní místa,
Aquapark,
Armáda,
Aukce,
Autobusové nádraží,
Autosalon,
Autoškola,
Banka,
Bankovní účet,
Bazar,
Bezpečnostní agentura,
Blog,
Botanická zahrada,
Burza,
Catering,
Cestovní kancelář,
Cukrárna,
Cvičiště pro psy,
Čajovna,
Čerpací stanice,
Dálniční poplatky,
Darování zážitků,
Deskové hry,
Detekce plagiátů,
Diskuzní fórum,
Divadelní hry,
Divadlo,
Dodávka vody,
Docházkový systém,
Dopravní dispečink,
Dopravní nehody,
Dopravní podnik,
Dopravní uzavírky,
Doručování zásilek,
Dotační programy,
Ekologické centrum,
Elektronická evidence tržeb,
Elektronické recepty,
Evidence smluv,
Evidence součástek,
Evidence zaměstnanců,
Exekuce,
Farmářské trhy,
Filmy,
Finanční poradenství,
Finanční trhy,
Finanční úřad,
Fitness centrum,
Fotbalová liga,
Fotbalový tým,
Fotoalbum,
Galerie,
Golfové kluby,
Grantová agentura,
Hardware,
Hobby market,
Hodinový manžel,
Hokejová liga,
Horská služba,
Hotel,
Hrady a zámky,
Hřbitov,
Hudební festival,
Hudební nástroje,
Hudební produkce,
Jaderná elektrárna,
Jazyková škola,
Jazykové pobyty,
Jednání zastupitelstva,
Jeskyně,
Jídelníček,
Jízdenky na autobus,
Jízdní řády,
Jurský park,
Kadeřnický salon,
Kamionová doprava,
Kasino,
Katastr nemovitostí,
Kavárna,
Kino,
Kniha jízd,
Knihkupectví,
Knihovna,
Konference,
Koňské dostihy,
Koupaliště,
Kravín,
Kuchařka,
Kurýrní služba,
Kurzy vaření,
Laboratoř,
Lékárna,
Lékařská karta pacienta,
Léky,
Lesní školka,
Letecká společnost,
Letecká záchranná služba,
Letiště,
Letní tábor,
Logistická firma,
Logistické centrum,
Logistický sklad,
Loterie,
Lyžařská škola,
Lyžařský areál,
Márnice,
Mateřská škola,
Menzy,
Městská hromadná doprava,
Městské exkurze,
Mobilní operátor,
Mobilní telefony,
Modely vláčků,
Multifunkční aréna,
Muniční sklad,
Muzeum,
Mýtné brány,
Nabídky dovolené,
Nabídky práce,
Nadnárodní společnost,
Náhradní díly,
Národní park,
Nebankovní půjčky,
Nemocnice,
Nutriční hodnoty,
Obchodní centrum,
Obchodní rejstřík,
Očkování do ciziny,
Odevzdávání úkolů,
Online cvičení,
Online půjčovna seriálů,
Ordinace lékaře,
Orientační běh,
Osobní doklady,
Osobní trenér,
Parkoviště,
Pekárna,
Personální agentura,
Pěstounská péče,
Pivovar,
Pizzerie,
Plánovací kalendář,
Plánování schůzek,
Platební karty,
Plavecký bazén,
Pneuservis,
Počítačové hry,
Pohádky,
Pojišťovna,
Policejní databáze,
Politické strany,
Populární hudba,
Porodnice,
Poslanecká sněmovna,
Pošta,
Potravinová banka,
Požární ochrana,
Pracovní úřad,
Provoz metra,
Průmyslová zóna,
Předpověď počasí,
Přepravní kontrola,
Přírodní rezervace,
Přístupový systém,
Psí útulek,
Psychiatrická léčebna,
Půjčovna auta,
Půjčovna lodí,
Půjčovna svatebních šatů,
Realitní agentura,
Redakční systém,
Registr obyvatel,
Regulační poplatky,
Restaurace,
Rezervace letenek,
Rezervace místností,
Rezervace ubytování,
Rezervace v restauraci,
Rozvodná síť,
Rozvoz jídla,
Rybářské potřeby,
Řízení letecké dopravy,
Řízení projektů,
Sázková kancelář,
Sbírka zákonů,
Sdílená kola,
Sdílené cestování,
Síť bankomatů,
Síť multikin,
Skautské středisko,
Sklad nápojů,
Skládka,
Sklárna,
Sociální dávky,
Sociální síť,
Soudní řízení,
Spalovna,
Spediční firma,
Společenství vlastníků jednotek,
Sportovní klub,
Sportovní turnaj,
Správa objektů,
Správce financí,
Srovnávač ubytování,
Stáj,
Státy světa,
Stavební řízení,
Stavebnice lego,
Stavebniny,
Střední škola,
Střelnice,
Studijní materiály,
Studijní systém,
Supermarket,
Světové dědictví,
Svoz a likvidace odpadů,
Symfonický orchestr,
Šachová databáze,
Taneční škola,
Taxi služba,
Televizní program,
Televizní seriály,
Třídní kniha,
Turistické cesty,
Turistický oddíl,
Turistický ruch,
Ubytování v soukromí,
Uprchlický tábor,
Úschovna zavazadel,
Územní plán,
Válečné konflikty,
Včelař,
Večerka,
Vědecké projekty,
Vědecké publikace,
Velkochov drůbeže,
Velkoobchod,
Veřejná zeleň,
Veřejné zakázky,
Vesmír,
Veterinární klinika,
Vězení,
Videopůjčovna,
Virtuální prohlídky,
Víza,
Vlakové nádraží,
Vojenský prostor,
Volby,
Volnočasové aktivity,
Vozový park,
Vrakoviště,
Vydavatelství novin,
Výkaz práce,
Výrobní procesy,
Vysokoškolská kolej,
Výstava,
Výstaviště,
Výtvarná díla,
Vývoj softwaru,
Vzdělávací instituce,
Webhosting,
Webový obchod,
Zábavní centrum,
Zahrádkářská kolonie,
Zahradnictví,
Záchytka,
Zastavárna,
Zbraně,
Zdravotní pojišťovna,
Zdravotní úhrady,
Zemědělská výroba,
Zimní úklid komunikací,
Zoologická zahrada,
Zpravodajská služba,
Žákovská knížka,
Železniční síť
- Nevertheless, the following topics are not allowed this semester
- Movies, actors
- Airport, flights
Exam Requirements
NoSQL Introduction
- Big Data and NoSQL terms, V characteristics (volume, variety, velocity, veracity, value, validity, volatility), current trends and challenges (Big Data, Big Users, processing paradigms, ...), principles of relational databases (functional dependencies, normal forms, transactions, ACID properties); types of NoSQL systems (key-value, wide column, document, graph, ...), their data models, features and use cases; common features of NoSQL systems (aggregates, schemalessness, scaling, flexibility, sharding, replication, automated maintenance, eventual consistency, ...)
Data Formats
- XML: constructs (element, attribute, text, ...), content model (empty, text, elements, mixed), entities, well-formedness; document and data oriented XML
- JSON: constructs (object, array, value), types of values (strings, numbers, ...); BSON: document structure (elements, type selectors, property names and values)
- RDF: data model (resources, referents, values), triples (subject, predicate, object), statements, blank nodes, IRI identifiers, literals (types, language tags); graph representation (vertices, edges); N-Triples notation (RDF file, statements, triple components, literals, IRI references); Turtle notation (TTL file, prefix definitions, triples, object and predicate-object lists, blank nodes, prefixed names, literals)
- CSV: constructs (document, header, record, field)
- Protocol Buffers: components (interface description language, source code compiler, binary serialization format), intended usage; schema structure (messages, enumerations), message fields (rules, types, names, tags)
XML Databases
- Native XML databases vs. XML-enabled relational databases; data model (XDM): tree (nodes for document, elements, attributes, texts, ...), document order, reverse document order, sequences, atomic values, singleton sequences
- XPath language: path expressions (relative vs. absolute, evaluation algorithm), path step (axis, node test, predicates), axes (forward: child, descendant, following, ...; reverse: parent, ancestor, preceding, ...; attribute), node tests, predicates (path conditions, position testing, ...), abbreviations
- XQuery language: path expressions, direct constructors (elements, attributes, nested queries, well-formedness), computed constructors (dynamic names), FLWOR expressions (for, let, where, order by, and return clauses), typical FLWOR use cases (joining, grouping, aggregation, integration, ...), conditional expressions (if, then, else), switch expressions (case, default, return), universal and existential quantified expressions (some, every, satisfies), comparisons (value, general, node; errors), atomization of values (elements, attributes)
RDF Stores
- Linked Data: principles (identification, standard formats, interlinking, open license), Linked Open Data Cloud
- SPARQL: graph pattern matching (solution sequence, solution, variable binding, compatibility of solutions), graph patterns (basic, group, optional, alternative, graph, minus); prologue declarations (BASE, PREFIX clauses), SELECT queries (SELECT, FROM, and WHERE clauses), query dataset (default graph, named graphs), variable assignments (BIND), FILTER constraints (comparisons, logical connectives, accessors, tests, ...), solution modifiers (DISTINCT, REDUCED; aggregation: GROUP BY, HAVING; sorting: ORDER BY, LIMIT, OFFSET), query forms (SELECT, ASK, DESCRIBE, CONSTRUCT)
MapReduce
- Programming models, paradigms and languages; parallel programming models, process interaction (shared memory, message passing, implicit interaction), problem decomposition (task parallelism, data parallelism, implicit parallelism)
- MapReduce: programming model (data parallelism, map and reduce functions), cluster architecture (master, workers, message passing, data distribution), map and reduce functions (input arguments, emission and reduction of intermediate key-value pairs, final output), data flow phases (mapping, shuffling, reducing), input parsing (input file, split, record), execution steps (parsing, mapping, partitioning, combining, merging, reducing), combine function (commutativity, associativity), additional functions (input reader, partition, compare, output writer), implementation details (counters, fault tolerance, stragglers, task granularity), usage patterns (aggregation, grouping, querying, sorting, ...)
- Apache Hadoop: modules (Common, HDFS, YARN, MapReduce), related projects (Cassandra, HBase, ...); HDFS: data model (hierarchical namespace, directories, files, blocks, permissions), architecture (NameNode, DataNode, HeartBeat messages, failures), replica placement (rack-aware strategy), FsImage (namespace, mapping of blocks, system properties) and EditLog structures, FS commands (ls, mkdir, ...); MapReduce: architecture (JobTracker, TaskTracker), job implementation (Configuration; Mapper, Reducer, and Combiner classes; Context, write method; Writable and WritableComparable interfaces), job execution schema
NoSQL Principles
- Scaling: scalability definition; vertical scaling (scaling up/down), pros and cons (performance limits, higher costs, vendor lock-in, ...); horizontal scaling (scaling out/in), pros and cons, network fallacies (reliability, latency, bandwidth, security, ...), cluster architecture; design questions (scalability, availability, consistency, latency, durability, resilience)
- Distribution models: sharding: idea, motivation, objectives (balanced distribution, workload, ...), strategies (mapping structures, general rules), difficulties (evaluation of requests, changing cluster structure, obsolete or incomplete knowledge, network partitioning, ...); replication: idea, motivation, objectives, replication factor, architectures (master-slave and peer-to-peer), internal details (handling of read and write requests, consistency issues, failure recovery), replica placement strategies; mutual combinations of sharding and replication
- CAP theorem: CAP guarantees (consistency, availability, partition tolerance), CAP theorem, consequences (CA, CP and AP systems), consistency-availability spectrum, ACID properties (atomicity, consistency, isolation, durability), BASE properties (basically available, soft state, eventual consistency)
- Consistency: strong vs. eventual consistency; write consistency (write-write conflict, context, pessimistic and optimistic strategies), read consistency (read-write conflict, context, inconsistency window, session consistency), read and write quora (formulae, motivation, workload balancing)
Key-Value Stores
- Data model (key-value pairs), key management (real-world identifiers, automatically generated, structured keys, prefixes), basic CRUD operations, use cases, representatives, extended functionality (MapReduce, TTL, links, structured store, ...)
- Riak: data model (buckets, objects, metadata headers); HTTP interface, cURL tool (options); CRUD operations (POST, PUT, GET, and DELETE methods, structure of URLs, data, headers), buckets operations (buckets, keys, properties); links (definition, headers, tags, link walking, navigational steps: bucket, tag and keep components), data types (Convergent Replicated Data Types: register, flag, counter, set, map; conflict resolution policies; usage restrictions), Search 2.0 Yokozuna (architecture; indexation and query evaluation processes; extractors: text, XML, JSON; SOLR document: extracted and technical fields; indexing schema: tokens, triples; full-text index creation, association and usage; query patterns: wildcards, ranges, ...); causal context (motivation, low-level techniques: timestamps, vector clocks, ...); vector clocks (logical clocks, vector of clocks, message passing); Riak Ring (physical vs. virtual nodes, consistent hashing, partitions, replica placement strategy, hinted handoff, handling of read and write requests)
- Redis: features (in-memory, data structure store), data model (databases, objects), data types (string, list, set, sorted set, hash), string commands (SET, GET, APPEND, SETRANGE, INCR, DEL, ...), list commands (LPUSH, RPUSH, LPOP, RPOP, LINDEX, LRANGE, LREM, ...), set commands (SADD, SISMEMBER, SUNION, SINTER, SDIFF, SREM, ...), sorted set commands (ZADD, ZRANGE, ZRANGEBYSCORE, ZINCRBY, ZREM, ...), hash commands (HSET, HMSET, HGET, HMGET, HKEYS, HVALS, HDEL, ...), general commands (EXISTS, KEYS, DEL, RENAME, ...), time-to-live commands (EXPIRE, TTL, PERSIST)
Wide Column Stores
- Data model (column families, rows, columns), query patterns, use cases, representatives
- Cassandra: data model (keyspaces, tables, rows, columns), primary keys (partition key, clustering columns), column values (missing; empty; native data types, tuples, user-defined types; collections: lists, sets, maps; frozen mode), additional data (TTL, timestamp); CQL language: DDL statements: CREATE KEYSPACE (replication options), DROP KEYSPACE, USE keyspace, CREATE TABLE (column definitions, usage of types, primary key), DROP TABLE, TRUNCATE TABLE; native data types (int, varint, double, boolean, text, timestamp, ...); literals (atomic, collections, ...); DML statements: SELECT statements (SELECT, FROM, WHERE, GROUP BY, ORDER BY, and LIMIT clauses; DISTINCT modifier; selectors; non/filtering queries, ALLOW FILTERING mode; filtering relations; aggregates; restrictions on sorting and aggregation), INSERT statements (update parameters: TTL, TIMESTAMP), UPDATE statements (assignments; modification of collections: additions, removals), DELETE statements (deletion of rows, removal of columns, removal of items from collections)
Document Stores
- Data model (documents), query patterns, use cases, representatives
- MongoDB: data model (databases, collections, documents, field names), document identifiers (features, ObjectId), data modeling (embedded documents, references); CRUD operations (insert, update, save, remove, find); insert operation (management of identifiers); update operation: replace vs. update mode, multi option, upsert mode, update operators (field: $set, $rename, $inc, ...; array: $push, $pop, ...); save operation (insert vs. replace mode); remove operation (justOne option); find operation: query conditions (value equality vs. query operators), query operators (comparison: $eq, $ne, ...; element: $exists; evaluation: $regex, ...; logical: $and, $or, $not; array: $all, $elemMatch, ...), dot notation (embedded fields, array items), querying of arrays, projection (positive, negative), projection operators (array: $slice, $elemMatch), modifiers (sort, skip, limit); MapReduce (map function, reduce function, options: query, sort, limit, out); primary and secondary index structures (index types: value, hashed, ...; forms; properties: unique, partial, sparse, TTL)
Graph Databases
- Data model (property graphs), use cases, representatives
- Neo4j: data model (graph, nodes, relationships, directions, labels, types, properties), properties (fields, atomic values, arrays); embedded database mode; traversal framework: traversal description, order (breadth-first, depth-first, branch ordering policies), expanders (relationship types, directions), uniqueness (NODE_GLOBAL, RELATIONSHIP_GLOBAL, ...), evaluators (INCLUDE/EXCLUDE and CONTINUE/PRUNE results; predefined evaluators: all, excludeStartPosition, ...; custom evaluators: evaluate method), traverser (starting nodes, iteration modes: paths, end nodes, last relationships); Java interface (labels, types, nodes, relationships, properties, transactions); Cypher language: graph matching (solutions, variable bindings); query sub/clauses (read, write, general); path patterns, node patterns (variable, labels, properties), relationship patterns (variable, types, properties, variable length); MATCH clause (path patterns, WHERE conditions, uniqueness requirement, OPTIONAL mode); RETURN clause (DISTINCT modifier, ORDER BY, LIMIT, SKIP subclauses, aggregation); WITH clause (motivation, subclauses); write clauses: CREATE, DELETE (DETACH mode), SET (properties, labels), REMOVE (properties, labels); query structure (chaining of clauses, query parts, restrictions)
Advanced Aspects
- Graph databases: non/transactional databases, query patterns (CRUD, graph algorithms, graph traversals, graph pattern matching, similarity querying); data structures (adjacency matrix, adjacency list, incidence matrix, Laplacian matrix), graph traversals, data locality (BFS layout, matrix bandwidth, bandwidth minimization problem, Cuthill-McKee algorithm), graph partitioning (1D partitioning, 2D partitioning, BFS evaluation), graph matching (sub-graph, super-graph patterns), non/mining based indexing
- Transactions: business vs. system transactions, local vs. distributed transactions, optimistic vs. pessimistic offline locks
- Performance tuning: scalability goals (reduce latency, increase throughput), Amdahl's law, Little's law, message cost model
- Visualization: motivation, visualization types (scatter plot, matrix chart, network diagram, correlation matrix, dendrogram, bar chart, histogram, box plot, bubble chart, line graph, stack graph, pie chart, treemap, tag cloud, arc diagram, centralized burst, globe, radial chart)
- Polyglot persistence
Recommended Literature
- Holubová, Irena - Kosek, Jiří - Minařík, Karel - Novák, David: Big Data a NoSQL databáze.
ISBN: 978-80-247-5466-6 (hardcover), 978-80-247-5938-8 (eBook PDF), 978-80-247-5939-5 (eBook EPUB).
Grada Publishing, a.s., 2015.
- Sadalage, Pramod J. - Fowler, Martin: NoSQL Distilled.
ISBN: 978-0-321-82662-6.
Pearson Education, Inc., 2013.
- Wiese, Lena: Advanced Data Management: For SQL, NoSQL, Cloud and Distributed Databases.
ISBN: 978-3-11-044140-6 (hardcover), 978-3-11-044141-3 (eBook PDF), 978-3-11-043307-4 (eBook EPUB).
DOI: 10.1515/9783110441413.
Walter de Gruyter GmbH, 2015.
- Zomaya, Albert Y. - Sakr, Sherif: Handbook of Big Data Technologies.
ISBN: 978-3-319-49339-8 (hardcover), 978-3-319-49340-4 (eBook).
DOI: 10.1007/978-3-319-49340-4.
Springer International Publishing AG, 2017.