Algorithms and Data Structures for Massive Datasets

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文档列表

029. Chapter 6. Streaming data Bringing everything together.mp4 46.8 MB
035. Chapter 7. Sampling from data streams.mp4 44.9 MB
047. Chapter 8. Quantile queries with q-digests.mp4 42.4 MB
038. Chapter 7. Sampling from a sliding window.mp4 40.7 MB
037. Chapter 7. Biased reservoir sampling.mp4 39.5 MB
008. Chapter 2. Usage scenarios in modern systems.mp4 38.4 MB
049. Chapter 9. Introducing the external memory model.mp4 38.4 MB
007. Chapter 2. Review of hash tables and modern hashing.mp4 37.4 MB
022. Chapter 4. Range queries with count-min sketch.mp4 37.0 MB
020. Chapter 4. Update.mp4 36.1 MB
034. Chapter 6. Biased sampling strategy.mp4 34.0 MB
019. Chapter 4. Frequency estimation and count-min sketch.mp4 33.0 MB
060. Chapter 10. Lookups.mp4 32.8 MB
009. Chapter 2. Collision resolution Theory vs. practice.mp4 32.6 MB
036. Chapter 7. Reservoir sampling.mp4 32.3 MB
061. Chapter 10. Log-structured merge-trees (LSM-trees).mp4 32.1 MB
012. Chapter 3. Approximate membership Bloom and quotient filters.mp4 32.0 MB
046. Chapter 8. Q-digest.mp4 31.9 MB
052. Chapter 9. Optimal searching.mp4 31.9 MB
041. Chapter 8. Approximate quantiles on data streams.mp4 31.6 MB
045. Chapter 8. Merging t-digests.mp4 30.8 MB
067. Chapter 11. Finding good enough pivots.mp4 30.6 MB
057. Chapter 10. Delete.mp4 30.5 MB
024. Chapter 5. HyperLogLog incremental design.mp4 30.1 MB
032. Chapter 6. Practical constraints and concepts in data streams.mp4 29.6 MB
031. Chapter 6. Deduplication.mp4 29.4 MB
040. Chapter 7. Sampling algorithms comparison.mp4 28.7 MB
011. Chapter 2. Adding a new noderesource.mp4 28.2 MB
001. Chapter 1. Introduction.mp4 28.1 MB
055. Chapter 10. Data structures in this chapter.mp4 27.6 MB
027. Chapter 5. The effect of the number of buckets (m).mp4 26.5 MB
004. Chapter 1. The structure of this book.mp4 26.4 MB
033. Chapter 6. Math bit Sampling and estimation.mp4 25.9 MB
025. Chapter 5. LogLog.mp4 25.9 MB
013. Chapter 3. A simple implementation.mp4 25.4 MB
039. Chapter 7. Priority sampling.mp4 25.2 MB
065. Chapter 11. External memory merge-sort (MB-way merge-sort).mp4 25.1 MB
059. Chapter 10. Bε-trees.mp4 24.9 MB
015. Chapter 3. Bloom filter adaptations and alternatives.mp4 24.7 MB
030. Chapter 6. Streaming data system A meta example.mp4 24.7 MB
016. Chapter 3. Understanding metadata bits.mp4 24.5 MB
023. Chapter 5. Cardinality estimation and HyperLogLog.mp4 24.3 MB
058. Chapter 10. Math bit Why are B-tree lookups optimal in external memory.mp4 23.5 MB
044. Chapter 8. Scale functions.mp4 23.3 MB
042. Chapter 8. Approximate quantiles.mp4 23.3 MB
066. Chapter 11. What about external quick-sort.mp4 23.2 MB
063. Chapter 11. External memory sorting.mp4 22.5 MB
003. Chapter 1. How to solve it, take two A book walkthrough.mp4 22.5 MB
005. Chapter 1. Latency vs. bandwidth.mp4 22.2 MB
054. Chapter 10. Data structures for databases B-trees, Bε-trees, and LSM-trees.mp4 22.1 MB
017. Chapter 3. Python code for lookup.mp4 21.9 MB
051. Chapter 9. Example 2 Binary search.mp4 21.6 MB
010. Chapter 2. Hash tables for distributed systems Consistent hashing.mp4 21.5 MB
056. Chapter 10. B-tree balancing.mp4 21.3 MB
050. Chapter 9. Example 1 Finding a minimum.mp4 21.1 MB
018. Chapter 3. Comparison between Bloom filters and quotient filters.mp4 20.6 MB
062. Chapter 10. LSM-tree cost analysis.mp4 20.2 MB
021. Chapter 4. Error vs. space in count-min sketch.mp4 20.2 MB
043. Chapter 8. T-digest How it works.mp4 19.4 MB
026. Chapter 5. Use case Catching worms with HLL.mp4 19.3 MB
014. Chapter 3. A bit of theory.mp4 18.1 MB
064. Chapter 11. Challenges of sorting in external memory An example.mp4 17.9 MB
002. Chapter 1. An example How to solve it.mp4 17.4 MB
053. Chapter 9. External memory model Simple or simplistic.mp4 17.3 MB
006. Part 1. Hash-based sketches.mp4 6.6 MB
048. Part 3. Data structures for databases and external memory algorithms.mp4 6.1 MB
028. Part 2. Real-time analytics.mp4 5.7 MB
Algorithms-and-Data-Structures-for-Massive-Datasets-Video-Edition.jpg 40.4 kB

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