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[ DevCourseWeb com ] Distributed Databases with Apache Ignite
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01 - Introduction
01 - Overview of Apache Ignite.mp4
01 - Overview of Apache Ignite.srt
02 - 1. Getting Started with Apache Ignite
01 - Memory-centric architecture.mp4
01 - Memory-centric architecture.srt
02 - The Ignite data model.mp4
02 - The Ignite data model.srt
03 - Running a single node Ignite cluster.mp4
03 - Running a single node Ignite cluster.srt
04 - Exploring the Ignite node running in Docker.mp4
04 - Exploring the Ignite node running in Docker.srt
05 - Running an in-memory Ignite cluster.mp4
05 - Running an in-memory Ignite cluster.srt
06 - Connect to Apache Ignite using DBeaver.mp4
06 - Connect to Apache Ignite using DBeaver.srt
03 - 2. Storing and Monitoring Data
01 - Working with in-memory data.mp4
01 - Working with in-memory data.srt
02 - Running a cluster with native persistence enabled.mp4
02 - Running a cluster with native persistence enabled.srt
03 - Persistent storage in an Ignite cluster.mp4
03 - Persistent storage in an Ignite cluster.srt
04 - Running a multi-node Ignite cluster.mp4
04 - Running a multi-node Ignite cluster.srt
05 - Configuring monitoring using GridGain.mp4
05 - Configuring monitoring using GridGain.srt
06 - Monitoring clusters with GridGain.mp4
06 - Monitoring clusters with GridGain.srt
04 - 3. Data Partitioning and Replication
01 - Data partitioning and replication.mp4
01 - Data partitioning and replication.srt
02 - Creating partitioned tables with affinity keys.mp4
02 - Creating partitioned tables with affinity keys.srt
03 - Handling partition losses.mp4
03 - Handling partition losses.srt
04 - Creating tables with backups.mp4
04 - Creating tables with backups.srt
05 - Handling partition losses with backups.mp4
05 - Handling partition losses with backups.srt
06 - Creating tables with replication.mp4
06 - Creating tables with replication.srt
07 - Handling partition losses with replication.mp4
07 - Handling partition losses with replication.srt
05 - 4. Running SQL Queries and Bulk Loading Data
01 - Resetting back to Ignite version 2.14.0.mp4
01 - Resetting back to Ignite version 2.14.0.srt
02 - Setting up for bulk loading of data.mp4
02 - Setting up for bulk loading of data.srt
03 - Bulk loading data using a SQL script.mp4
03 - Bulk loading data using a SQL script.srt
04 - Bulk loading data using COPYINTO.mp4
04 - Bulk loading data using COPYINTO.srt
05 - Bulk loading data using streaming mode.mp4
05 - Bulk loading data using streaming mode.srt
06 - Indexing.mp4
06 - Indexing.srt
06 - 5. Programmatically Accessing Ignite with Python
01 - Using the cache API with pyignite.mp4
01 - Using the cache API with pyignite.srt
02 - Populating complex data types in the cache.mp4
02 - Populating complex data types in the cache.srt
03 - Retrieving complex data from the cache.mp4
03 - Retrieving complex data from the cache.srt
04 - Configuring cache expiry.mp4
04 - Configuring cache expiry.srt
05 - Configuring cache consistency modes.mp4
05 - Configuring cache consistency modes.srt
06 - Client failover.mp4
06 - Client failover.srt
07 - Conclusion
01 - Summary and next steps.mp4
01 - Summary and next steps.srt
Bonus Resources.txt
Ex_Files_Distributed_Databases_with_Apache_Ignite
Exercise Files
demo01_apache_ignite_setup
demo01_apache_ignite_setup.sh
demo02_persistence
demo02_persistence.sh
my_schema.xml
demo03_partitioning_backup
demo03_partitioning_backup.sh
demo04_replication
demo04_replication.sh
demo05_commit_and_rollback
demo05_commit_and_rollback.sh
demo06_operational_commands_for_data_loading
bulk_loading
transactions.csv
transactions.sql
demo06_operational_commands_for_data_loading.sh
demo07_indexing
demo07_indexing.sh
demo08_aggregrate_functions
demo08_aggregrate_functions.sh
demo09_cache_api_pyignite
code
caching_v01.py
caching_v02.py
caching_v03.py
caching_v04.py
caching_v05.py
caching_v06.py
caching_v07.py
caching_v08.py
caching_v09.py
querying_v07.py
datasets
credits.csv
titles.csv
demo09_cache_api_pyignite.sh
demo10_client_failover
code
client_failover.py
demo10_client_failover.sh
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