Optimize HLS playlist parsing by caching regex Matchers

[mbolaris]

Introduce a per-parse regex Matcher cache in HlsPlaylistParser to significantly reduce object allocation overhead during playlist parsing.

Problem:
Each Matcher object allocates memory in BOTH Java heap and native heap, creating two critical issues in production:

1. Native heap exhaustion: Native allocations are substantial and not subject to normal Java GC pressure. When Matcher objects are created faster than they're garbage collected, the native heap can be exhausted even when Java heap has space available, causing OutOfMemoryError in the native allocator.

2. GC-induced ANRs: Excessive Matcher allocation causes frequent GC cycles. This is particularly severe with MultiView feature (4 concurrent playback sessions) on lower-performance devices, where sustained GC pressure from thousands of short-lived Matcher objects causes Application Not Responding (ANR) events.

Both issues are exacerbated by frequent HLS playlist refreshes (every 2-6 seconds), creating continuous allocation pressure.

Solution:

• Instantiate a MatcherCacheState per parse() call and pass it through private parsing helpers (no ThreadLocal, clear ownership/lifetime)
• Employ access-ordered LinkedHashMap as LRU cache (max 32 entries)
• Reuse Matcher objects via reset() instead of creating new instances
• Eliminate both Java heap AND native heap allocation pressure

Performance impact:

• Reduces Matcher allocations by >99% in production workloads
• Eliminates native heap exhaustion risk from Matcher object churn
• Drastically reduces GC frequency and duration, preventing ANRs
• Typical cache occupancy: 6-12 patterns (well under 32 limit)
• Critical for MultiView and lower-performance devices

Testing:

• Validated over 2+ hours with production HLS streams
• No functional changes to parsing behavior
• All existing tests pass