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    SIMULATION-BASED TECHNIQUES FOR EVALUATING ENCODING LADDERS FOR VIDEO STREAMING
    21.
    发明公开
    SIMULATION-BASED TECHNIQUES FOR EVALUATING ENCODING LADDERS FOR VIDEO STREAMING 审中-公开

    公开(公告)号：US20240244281A1

    公开(公告)日：2024-07-18

    申请号：US18154709

    申请日：2023-01-13

    Applicant: NETFLIX, INC.

    Inventor： Xiaoqing ZHU ,  Sagar Bharadwaj KALASIBAIL SEETHARAM ,  Te-Yuan HUANG ,  Kaylie Alexa KWON ,  Kyle Christopher SWANSON ,  Renata Cruz TEIXEIRA

    IPC: H04N21/647 ,  H04N21/238 ,  H04N21/84

    CPC classification number: H04N21/64738 ,  H04N21/238 ,  H04N21/84

    Abstract: In various embodiments, a simulation evaluation application generates a first streaming header based on rungs of a first candidate encoding ladder, where each rung specifies a resolution and a bitrate of a different encoded video. The simulation evaluation application executes an adaptive bitrate algorithm on the first streaming header based on a network throughput trace to determine a first value for a metric that is relevant to quality of experience. The simulation evaluation application generates a second streaming header based on a second candidate encoding ladder. The simulation evaluation application executes the adaptive bitrate algorithm on the second streaming header based on the network throughput trace to determine a second value for the first metric. The simulation evaluation application compares the first value to the second value to determine that the first candidate encoding ladder instead of the second candidate encoding ladder should be used to stream the media title.

    SYSTEMS AND METHODS FOR OPTIMIZING HARD DRIVE THROUGHPUT
    23.
    发明公开
    SYSTEMS AND METHODS FOR OPTIMIZING HARD DRIVE THROUGHPUT 审中-公开

    公开(公告)号：US20240095147A1

    公开(公告)日：2024-03-21

    申请号：US18523839

    申请日：2023-11-29

    Applicant: Netflix Inc.

    Inventor： David W. Pfitzner

    IPC: G06F11/34 ,  G06F11/22 ,  G06F11/30

    CPC classification number: G06F11/3485 ,  G06F11/2294 ,  G06F11/3058 ,  G06F11/3419

    Abstract: The disclosed computer-implemented method includes accessing a hard drive to measure operational characteristics of the hard drive. The method next includes deriving hard drive health factors used to control the hard drive that are based on the measured operational characteristics. The derived hard drive health factors include an average per-seek time indicating an average amount of time the hard drive spends seeking specified data that is to be read and an average read speed indicating an average amount of time the hard drive spends reading the specified data. The method next includes determining, based on the hard drive health factors and the operational characteristics, an amount of load servicing capacity currently available at the hard drive, and then includes regulating the amount of load servicing performed by the hard drive according to the determined amount of available load servicing capacity. Various other methods, systems, and computer-readable media are also disclosed.

    SYSTEMS AND METHODS FOR PREDICTING AND MITIGATING OUT OF MEMORY KILLS
    26.
    发明公开
    SYSTEMS AND METHODS FOR PREDICTING AND MITIGATING OUT OF MEMORY KILLS 审中-公开

    公开(公告)号：US20240028432A1

    公开(公告)日：2024-01-25

    申请号：US18354582

    申请日：2023-07-18

    Applicant: Netflix, Inc.

    Inventor： Andrew David Eichacker ,  Anselm Lau ,  Aryan Mehra ,  Jason Nicholas Munning ,  Farnaz Karimdady Sharifabad ,  Prasanna Vijayanathan ,  Chaïna Wade

    IPC: G06F11/00 ,  G06F9/50

    CPC classification number: G06F11/008 ,  G06F9/5016

    Abstract: A computer-implemented method includes identifying static information associated with a computing device that is running a media playback application. The method also includes monitoring the media playback application during a playback session to identify dynamic information associated with the playback session. Still further, the method includes instantiating a trained machine learning (ML) model to determine, based on historical usage data associated with the media playback application, a likelihood that the media playback application will experience an out of memory kill. The trained ML model implements a graded window to indicate a scaled likelihood that an out of memory kill will occur within a specified timeframe. Then, according to the trained ML model's determination, the method generates a prediction that an out of memory kill will occur for the media playback application within the specified timeframe. Various other methods, systems, and computer-readable media are also disclosed.

    Watermark-based techniques for change-data-capture
    27.
    发明授权
    Watermark-based techniques for change-data-capture 有权

    公开(公告)号：US11860849B2

    公开(公告)日：2024-01-02

    申请号：US17745739

    申请日：2022-05-16

    Applicant: NETFLIX, INC.

    Inventor： Andreas Andreakis ,  Ioannis Papapanagiotou

    IPC: G06F16/00 ,  G06F16/23

    CPC classification number: G06F16/2358 ,  G06F16/2308 ,  G06F16/2365

    Abstract: Various embodiments set forth systems and techniques for concurrent log and dump processing. The techniques include selecting, from a datastore, a chunk comprising one or more rows of data; comparing the one or more rows of data in the chunk with a first set of log events in a change log associated with the datastore, wherein each log event included in the first set of log events occurs after a first log event in the change log and prior to a second log event in the change log; selecting, based on the comparison, one or more non-conflicting rows in the chunk; and transmitting, to an output, one or more log events associated with the one or more non-conflicting rows in the chunk prior to processing a second set of log events in the change log, wherein the second set of log events occur after the second log event.

    COOPERATIVE COMPRESSION IN DISTRIBUTED DATABASES
    29.
    发明公开
    COOPERATIVE COMPRESSION IN DISTRIBUTED DATABASES 审中-公开

    公开(公告)号：US20230344446A1

    公开(公告)日：2023-10-26

    申请号：US18304242

    申请日：2023-04-20

    Applicant: NETFLIX, INC.

    Inventor： Joseph LYNCH

    IPC: H03M7/30

    CPC classification number: H03M7/3088

    Abstract: In various embodiments a computer-implemented method for managing use of a shared compression dictionary in a distributed database environment. The method includes determining that a given version of the shared compression dictionary should be designated as a current primary version of the shared compression dictionary. The method also includes receiving, from a client device, first write data compressed with a previous primary version of the shared compression dictionary and in response to receiving the first write data, transmitting, to the client device, the current primary version of the shared compression dictionary and an instruction to compress new write data with the current primary version of the shared compression dictionary. Additionally, the method includes receiving, from the client device, a second write data compressed with the current primary version of the shared compression dictionary and storing the second write data in a database.

    TECHNIQUES FOR AUTOMATICALLY INFERRING INTENTS OF SEARCH QUERIES
    30.
    发明公开
    TECHNIQUES FOR AUTOMATICALLY INFERRING INTENTS OF SEARCH QUERIES 审中-公开

    公开(公告)号：US20230334055A1

    公开(公告)日：2023-10-19

    申请号：US18299674

    申请日：2023-04-12

    Applicant: NETFLIX, INC.

    Inventor： Sudeep DAS ,  Ivan Gennadievich PROVALOV ,  Weidong ZHANG ,  Yi ZHANG

    IPC: G06F16/2457 ,  G06F16/28

    CPC classification number: G06F16/24578 ,  G06F16/285

    Abstract: In various embodiments, an intent-based query processing application processes search queries. The intent-based query processing application computes lexical similarity scores between a search query and a set of entities. The intent-based query processing application computes entity relevance scores based on the lexical similarity scores and user engagement scores associated with both the search query and the set of entities. The intent-based query processing application computes a first category relevance score associated with both the search query and a first category based on the entity relevance scores. The intent-based query processing application determines an intent associated with the search query based on the first category relevance score. The intent-based query processing application generates a response to the search query based on the intent.

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