• Annotation (source: SIS)
• Lecturer: Irena Holubová (irena.holubova (at) matfyz.cuni.cz)
• Tutor: Pavel Koupil (pavel.koupil (at) matfyz.cuni.cz)
• Lectures
• Schedule
  • Lectures: Wednesday 14:00 - 15:30 (room S5)
  • Practical classes: Thursday 17:20 - 18:50 (room SW2)
• Table with points

Study Materials: NDBI040_00_Introduction.pdf

Tools: ssh / scp (on macOS / Linux) or PuTTy / WinSCP (on Windows)

Study Materials: NDBI040_03_ApacheSpark.pdf

Maven project: ndbi040-wordCountSpark.zip, ndbi040-piEstimation.zip, ndbi040-actorsSpark.zip

Data file: actors.json

Solution: ndbi040-piEstimation-solved.zip, ndbi040-actorsSpark-solved.zip

Tools: NetBeans IDE, ssh / scp (on macOS / Linux) or PuTTy / WinSCP (on Windows)

Software requirements: Java JDK 8.x or newer

References:

• Apache Spark
• Quick Start
• RDD Programming Guide
• Spark SQL, DataFrames and Datasets Guide
• Submitting Applications
• Additional Spark Examples

Study Materials: NDBI040_05_RiakKV.pdf

Solution: solution_riakkv.txt

Recording: NDBI040_RiakKV.zip (MOV; 59.6 MiB; the password is still the same)

References:

• Riak KV Documentation
• Riak KV Search 2.0 Documentation
• Apache Solr Query Parser Documentation

Study Materials: NDBI040_05_MongoDB.pdf

Data file: data.js

Solution: solution_mongodb.txt

References:

• MongoDB 3.2.9 (installed on the NoSQL server)
• The MongoDB 3.2 Manual

Study Materials: NDBI040_07_PostgreSQL.pdf

Data file: data.txt

Solution: solution_postgresql.txt

Tools: Netbeans IDE, pgAdmin or psql (command line)

References:

• PostgreSQL 11.10 (installed on the NoSQL server)
• JSON Types
• JSON Functions and Operators
• Aggregate Functions

Study Materials: NDBI040_09_Elasticsearch.pdf

Data file: data.txt, bulk.txt

Solution: solution_elasticsearch.txt

References:

• Elasticsearch 7.10 (installed on the NoSQL server)
• Index API
• Mapping
• Mapping Types
• Document API
• Query DSL
• Aggregations

Presentation 7: Couchbase

Presentation 8: GridDB

Presentation 9: RavenDB

Presentation 10: Redis

Presentation 11: Tarantool

Presentation 12: YugabyteDB

• Select (multi-model) database system
  • Each student must select distinct database system (i.e., no two or more students are allowed to present the same database system)
  • This system must be reported to and explicitly accepted by the tutor
• Deploy the selected system on your computer
• Explore data models supported in the selected system
• Explore query language(s)
• Finally, prepare a presentation summarizing your observation:
  • Briefly intruduce the selected system
  • Present the structure of data model(s) and its combination (if applicable)
  • Shortly present query language(s) implemented by the selected system and show examples
    • I.e., demonstrate typical DDL and DML statements (e.g., create, insert, update, delete, projection, selection, aggregation, joining, set operations, sorting, modifying the result, nesting queries, etc.)
    • Or discuss the absence of particular query constructs
  • Discuss advantages and/or disadvantages of the selected system
• Each presentation will be strictly limited to 10 minutes (approximately 10 pages) and additional 3 minutes of discussion
• Submit your presentation in PDF format via email and wait for acceptance e-mail
• Recommended multi-model database systems:
  • Redis, MariaDB, Couchbase, MarkLogic, ArangoDB, Virtuoso, OrientDB, Oracle NoSQL, ScyllaDB, RavenDB, Apache Drill, YugabyteDB, MonetDB, Tarantool, Citus, GridDB, FoundationDB, CrateDB, NCache, GigaSpaces, SequoiaDB, TerminusDB, Bangdb, ArcadeDB, ...
  • see https://db-engines.com/en/ranking
• Points: up to 15 + 5 = 20
• Deadline for database system (topic) selection: 10. 3. 2022
• Deadline for submit of presentation: 3. 5. 2022 AoE
• Should any complications appear, do not hesitate to contant your tutor by e-mail to pavel.koupil (at) matfyz.cuni.cz