Summary of DA: Recommendation Systems

DA: Recommendation Systems - Netflix Project

The algorithms behind Netflix's recommendation system are the focus of this PBL, allowing students to implement a data analytics project from scratch.

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Mode	Cache item	Static	H	M	Primary store	H	M	S
Req	adhoc/core_filter_global_filters				default_request	0	1	1
App	core/capabilities	static accel.	264	1	redis2021	1	0	0
Ses	core/coursecat				redis2021	0	3	4
App	core/coursecattree	static accel.	2	2	redis2021	2	0	0
App	core/coursecontacts	static accel.	0	1	redis2021	0	1	1
App	core/coursemodinfo				Local Disk	2	0	0
App	core/databasemeta	static accel.	9	10	redis2021	10	0	0
App	core/eventinvalidation	static accel.	0	1	redis2021	1	0	0
App	core/fontawesomeiconmapping	static accel.	0	1	redis2021	1	0	0
App	core/htmlpurifier				Local Disk	6	0	0
App	core/langmenu	static accel.	5	1	APCu	1	0	0
Ses	core/navigation_expandcourse				redis2021	0	12	14
App	core/observers	static accel.	0	2	redis2021	2	0	0
App	core/plugin_functions	static accel.	0	12	redis2021	12	0	0
App	core/plugin_manager				redis2021	3	0	0
App	core/roledefs	static accel.	0	1	redis2021	1	0	0
App	core/string	static accel.	219	74	APCu	74	0	0
App	core/yuimodules				redis2021	3	0	0
App	tool_abconfig/experiments	static accel.	4	1	redis2021	1	0	0
App	tool_monitor/eventsubscriptions	static accel.	0	2	redis2021	2	0	0
Req	tool_policy/policy_optional				default_request	0	0	3

Store name	Cache store	H	M	S
static accel.		503	109	0
APCu	cachestore_apcu	75	0	0
Local Disk	cachestore_file	8	0	0
default_request	cachestore_static	0	1	4
redis2021	cachestore_redis	39	16	19
Total		625	126	23