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concept). Where the Nal_type value is less than 0x1, or greater than 0x5, indicates that this Nalu belongs to a slice. Check if it is SLICE if (I_nal_type After finding the nalu of slice, the data of Nalu can be calculated and calculated by byte, and the result is true to indicate the end position of this slice (frame of video frames). Determine if the frame ends for (uint32_t i = 3; i The above code is excerpt from FFmpeg. His actual role is to judge the slice inside the first_mb_in_slice, tha

RDD element is a string containing a JSON object.SC is an already existing sparkcontextval SqlContext = new Org.apache.spark.sql.SQLContext (SC)//A JSON dataset with a path indicated// This path can be either a separate text file or a directory that stores text files val Path = "Examples/src/main/resources/people.json"//Generates a SCHEMARDD Val based on the path indicated by the file People = Sqlcontext.jsonfile (path)//inferred pattern can be explicitly people.printschema ()//root//|--by usin

, Cust_zip, Cust_country, Cust_contact, Cust_email) VALUES (10001, ' Coyote Inc ', ' Maple Lane ', ' Detroit ', ' MI ', ' 44444 ', ' USA ', ' Y Lee ', ' [emailprotected ] INSERT into Customers (cust_id, Cust_name, cust_address, cust_city, Cust_state, Cust_zip, Cust_country, cust_contact VALUES (10002, ' Mouse House ', ' 333 fromage Lane ', ' Columbus ', ' OH ', ' 43333 ', ' USA ', ' Jerry Mouse '); INSERT into Customers (c ust_id, Cust_name, cust_addr

Library, which provides a good solution for reading, writing, and open source. It provides a basic interface for reading and writing code streams. For example, find NAL, exponential Columbus code, and so on. Therefore, using the open Source Library, just follow the syntax rules in the standard manual to one by one resolution. For this library, do not expand the description in detail here. 0, according to the standard manual syntax, establish a global

Dataframe will be: Of course you can use the hive Read method: Hivecontext.sql ("fromsrc SELECT key, value"). Sparksql Data Source: Json Sparksql supports reading data from a JSON file or a JSON-formatted RDD New Org.apache.spark.sql.SQLContext (SC) //can be a directory or a folderVal Path ="Examples/src/main/resources/people.json"val People=SqlContext.read.json (path)//The inferred schema can be visualized using the Printschema () method. People.printschema ()//Register This DataFrame as a ta