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UDEMY.Databricks.Certified.Associate.Developer.for.Apache.Spark.4.2026.BOOKWARE-MiMiR
UDEMY.Databricks.Certified.Associate.Developer.for.Apache.Spark.4.2026.BOOKWARE-MiMiR
Autre 🕐 27/06/2026 SCENE MiMiR SCENE 🌱 0 seed / 0 leech 📡 srrdb
0 seeds 0 leechs 0 o MiMiR 27/06/2026 20:39
🧠 Release Intelligence
10
Confidence
0
Quality
1
Sources
0
Relations
20%
Complete
👥 Team: MiMiR
20.6
Authority
413
Releases
BRONZE
Tier
2026-06-15
Last Release
Propagation (1 source)
Confidence
40%
20:39:56 🚀 SRRDB FIRST PRE
🎯 Confidence Breakdown
Scene Group reconnu +5
Fingerprint calculé +5
TOTAL: 10/100
🏛️ Source Authority
srrdb 50/100
First-to-pre: 99.6% Confirm: 0.5% Coverage: 89.46%
👪 Family (1 variant)
Release Res Codec Source Team Quality Size
UDEMY.Databricks.Certified.Associate.Developer.for.Apache.Spark.4 ⭐ SCENE MiMiR 25 26.5 GB
⚙️ Technical Metadata
🎬 Video
Source SCENE
📋 Info
Release Type srrdb
🔑 Identifiers
Fingerprint 8ba9e7aef29e568320f3… 📋
Master FP 1adf32a5a0b372dab7fe… 📋
📋 Raw JSON (click to expand)
📁 Release Contents
Stored files
"01-Course_Introduction_Resources\1-Introduction.mkv"124,241,831DD6B1C2E
"01-Course_Introduction_Resources\4-Course_Content_Structure_Overview.mkv"115,048,667BF96C4E6
"01-Course_Introduction_Resources\7-How_to_use_Notes.mkv"120,242,37057DCD54F
"02-Big_Data_and_3Vs\11-MapReduce_Framework.mkv"304,901,24186CDFBAD
"02-Big_Data_and_3Vs\8-What_is_Big_Data.mkv"122,936,122FA24CA80
"02-Big_Data_and_3Vs\9-Monolithic_VS_Distributed_Architecture.mkv"157,463,4166FDC5FD1
"03-Apache_Spark_Architecture_Setup\12-What_is_Apache_Spark.mkv"130,117,27067F07911
"03-Apache_Spark_Architecture_Setup\13-Spark_Architecture_Backbone.mkv"416,700,740180DF0E0
"03-Apache_Spark_Architecture_Setup\14-Spark_Session_VS_Spark_Context.mkv"170,456,522D189ED85
"03-Apache_Spark_Architecture_Setup\15-Databricks_Overview.mkv"344,826,24941B82B46
"03-Apache_Spark_Architecture_Setup\16-Unity_Catalog_Setup.mkv"742,123,0435DC262C4
"03-Apache_Spark_Architecture_Setup\18-Write_First_Spark_Code_Spark_Session.mkv"196,069,996F9FE4594
"04-Apache_Spark_Components\20-Inside_Driver_and_Worker_Nodes.mkv"126,222,736B0F5EE2D
"04-Apache_Spark_Components\21-Narrow_and_Wide_Transformations.mkv"331,693,609CF7382C0
"04-Apache_Spark_Components\22-Lazy_Evaluation.mkv"122,028,34946641FF9
"04-Apache_Spark_Components\23-Lazy_Evaluation_In_Action.mkv"217,838,22428D7DEFD
"04-Apache_Spark_Components\24-Catalyst_Optimizer_In_Spark.mkv"191,876,039BB15E7AC
"04-Apache_Spark_Components\25-Implement_Catalyst_Optimizer_in_Code.mkv"146,599,44992E5333D
"04-Apache_Spark_Components\26-Spark_Layers_Spark_RDDs.mkv"264,473,9234C12CC43
"04-Apache_Spark_Components\27-Why_Code_in_Dataframe_API.mkv"176,529,886E1AFA59A
"04-Apache_Spark_Components\28-Understand_Jobs_Stages_Tasks_In_Spark.mkv"217,965,10889C53BEF
"04-Apache_Spark_Components\29-Trigger_Jobs_and_Spark_UI.mkv"539,068,7419941E8E1
"04-Apache_Spark_Components\30-spark_submit_command.mkv"119,804,394303032A7
"04-Apache_Spark_Components\31-Jobs_Stages_and_Tasks_Flow.mkv"125,380,38735996C44
"04-Apache_Spark_Components\32-Coalesce_and_Repartition_For_Partitions.mkv"127,913,926BDBE56C8
"04-Apache_Spark_Components\34-Spark_Query_Plans.mkv"294,134,583DB5AAEE7
"05-PySpark_Transformations\35-Read_Files_With_PySpark.mkv"594,328,723712D94DF
"05-PySpark_Transformations\36-Read_Data_From_JDBC_Source.mkv"131,091,6423D47FDC8
"05-PySpark_Transformations\37-Handle_Malformed_Records.mkv"105,109,9784602C158
"05-PySpark_Transformations\38-Define_Schema_For_Raw_Data.mkv"244,217,951536C0F85
"05-PySpark_Transformations\41-FILTER_Transformation.mkv"254,526,585EF00CAED
"05-PySpark_Transformations\43-WITHCOLUMN.mkv"350,363,7561A4FB28E
"05-PySpark_Transformations\44-Type_Casting_Tranformations.mkv"126,225,02619457615
"05-PySpark_Transformations\45-Sorting_DataFrames.mkv"143,682,1083640BCF2
"05-PySpark_Transformations\48-DROPDUPLICATES.mkv"146,769,6778D9356D5
"05-PySpark_Transformations\49-UNION_UNIONBYNAME.mkv"162,127,623AF03CA84
"05-PySpark_Transformations\50-DATE_FUNCTIONS.mkv"214,702,931D7EACF9F
"05-PySpark_Transformations\51-STRING_FUNCTIONS.mkv"104,049,2082365BE85
"05-PySpark_Transformations\52-Handling_NULLS.mkv"252,321,114A91181CF
"05-PySpark_Transformations\53-SPLITTING_INDEXING.mkv"145,183,948C02D60B3
"05-PySpark_Transformations\54-EXPLODE.mkv"134,943,755091D558A
"05-PySpark_Transformations\56-GROUPBY.mkv"288,936,376793AFFFA
"05-PySpark_Transformations\58-COLLECT_LIST.mkv"104,132,6283A9CD559
"05-PySpark_Transformations\59-PIVOTING.mkv"141,394,94436B46009
"05-PySpark_Transformations\60-WHEN_OTHERWISE.mkv"185,796,012360D079A
"05-PySpark_Transformations\61-JOINS.mkv"491,549,06863499E1E
"05-PySpark_Transformations\62-WINDOW_FUNCTIONS.mkv"284,828,877D256C9FB
"05-PySpark_Transformations\63-CUMULATIVE_SUM.mkv"208,924,6308B704C04
"05-PySpark_Transformations\64-User_Defined_Functions_UDF.mkv"265,701,01370914989
"05-PySpark_Transformations\65-User_Defined_Table_Functions_UDTF.mkv"161,212,0120932B4F3
"05-PySpark_Transformations\67-Concatenation_Transformations.mkv"140,080,04664280F62
"05-PySpark_Transformations\68-Write_Output_Modes.mkv"359,794,2157ACCAB70
"05-PySpark_Transformations\70-Delta_Format_Open_Table_Format.mkv"165,785,57217A09ECF
"05-PySpark_Transformations\71-Upsert_In_PySpark.mkv"394,757,46422E60EF6
"05-PySpark_Transformations\72-Handling_Complex_JSON_Objects.mkv"262,053,20976A73B95
"05-PySpark_Transformations\73-File_Source_Modes.mkv"241,897,344ACCA0CF9
"06-Spark_SQL_Objects\74-Spark_SQL_and_Temporary_View.mkv"208,613,61262EA5D04
"06-Spark_SQL_Objects\76-Global_Temporary_Views.mkv"160,029,060898B697A
"06-Spark_SQL_Objects\79-Upsert_Method_in_Spark_SQL.mkv"352,522,7470D0A4294
"06-Spark_SQL_Objects\83-Spark_SQL_Scripting_Functions.mkv"111,814,951FC4B1DCA
"06-Spark_SQL_Objects\84-Spark_SQL_Auxiliary_Statements.mkv"376,010,9702BABE8C9
"06-Spark_SQL_Objects\85-Spark_SQL_Aggregate_Functions.mkv"349,291,171FA3C4DE8
"06-Spark_SQL_Objects\86-Struct_Map.mkv"145,626,2075A25A058
"06-Spark_SQL_Objects\87-Spark_SQL_Datetime_Functions.mkv"273,506,5696300B2BA
"06-Spark_SQL_Objects\88-Spark_SQL_Window_Functions.mkv"159,267,695C5666A7C
"06-Spark_SQL_Objects\89-Spark_SQL_Array_Functions.mkv"139,882,86944CABAEA
"06-Spark_SQL_Objects\90-Spark_SQL_Properties_Commands.mkv"139,515,668A8412DD1
"07-Shuffle_Sort_Merge_VS_Hash_VS_Broadcast_Joins\100-Trigger_Broadcast_Join_In_Code.mkv"109,447,0434029E01C
"07-Shuffle_Sort_Merge_VS_Hash_VS_Broadcast_Joins\96-Shuffle_Sort_Merge_Join.mkv"409,523,235443288A3
"07-Shuffle_Sort_Merge_VS_Hash_VS_Broadcast_Joins\97-Shuffle_Hash_Join.mkv"114,981,663FF17DCEB
"07-Shuffle_Sort_Merge_VS_Hash_VS_Broadcast_Joins\98-Spark_UI_for_Joins.mkv"109,230,133F8DEC0A4
"07-Shuffle_Sort_Merge_VS_Hash_VS_Broadcast_Joins\99-Broadcast_Join.mkv"262,199,699258FD34A
"08-Memory_Management_Deployment_Modes\101-Driver_Memory_Management.mkv"236,940,1175E7AD57C
"08-Memory_Management_Deployment_Modes\102-Why_How_Driver_OOM_Error.mkv"117,932,5278D5395FB
"08-Memory_Management_Deployment_Modes\103-Executor_Memory_Overview.mkv"200,006,3580DFC4BF0
"08-Memory_Management_Deployment_Modes\104-Executor_Memory_Managment.mkv"405,121,965E682B33E
"08-Memory_Management_Deployment_Modes\105-Executor_s_Unified_Memory.mkv"188,749,637809E810C
"08-Memory_Management_Deployment_Modes\106-Data_Spilling_In_Spark.mkv"127,034,9319354E3F7
"08-Memory_Management_Deployment_Modes\107-Why_and_How_Executor_OOM_Error.mkv"149,755,840C7EBAD2F
"08-Memory_Management_Deployment_Modes\109-Edge_Node_in_Spark.mkv"128,290,9005808D74C
"08-Memory_Management_Deployment_Modes\110-Deployment_Modes_in_Spark.mkv"166,007,690BA6B9E67
"09-AQE_Adaptive_Query_Execution\112-AQE_Coalesce.mkv"230,166,353B6F401E6
"09-AQE_Adaptive_Query_Execution\113-AQE_Split_Partitions.mkv"127,107,84472A8D60F
"09-AQE_Adaptive_Query_Execution\114-AQE_Joins_Strategy.mkv"126,836,5959E30D5BE
"10-Cache_and_Persist_in_Spark\115-Cache_Dataframes_in_Apache_Spark.mkv"212,659,82089075B2F
"10-Cache_and_Persist_in_Spark\116-Persist_Dataframes_in_Apache_Spark.mkv"157,979,371A24A0597
"10-Cache_and_Persist_in_Spark\117-Storage_Levels_For_Storing_Dataframes.mkv"137,861,4961CCC8314
"11-Partition_Pruning_Dynamic_Partition_Pruning\122-What_are_partitions_in_this_context.mkv"114,165,2306F796AED
"11-Partition_Pruning_Dynamic_Partition_Pruning\123-How_to_create_Partitions.mkv"134,293,058D409521A
"11-Partition_Pruning_Dynamic_Partition_Pruning\124-Why_Partition_Pruning.mkv"182,692,819B74AA297
"11-Partition_Pruning_Dynamic_Partition_Pruning\125-What_is_Dynamic_Partition_Pruning.mkv"218,736,162326FAD7A
"12-Salting_Broadcast_Variables_Accumulators\126-What_is_Salting.mkv"147,680,4898162AB8C
"12-Salting_Broadcast_Variables_Accumulators\127-Apply_Salting_in_Aggregate_Functions.mkv"156,058,48550F114E0
"12-Salting_Broadcast_Variables_Accumulators\128-What_is_Salting_in_Join_Operations.mkv"185,342,507F0BB5B99
"12-Salting_Broadcast_Variables_Accumulators\129-How_to_apply_Salting_with_JOINS.mkv"114,395,974B68A4908
"12-Salting_Broadcast_Variables_Accumulators\130-SQL_Hints_in_Spark.mkv"124,663,6940BAD44CF
"13-Garbage_Collection_Cycle_Bucketing\135-How_to_reduce_Garbage_Collection_Time.mkv"130,865,453EFEB50A6
"13-Garbage_Collection_Cycle_Bucketing\136-Executor_s_role_in_GC_Cycle.mkv"167,078,0534DDB8944
"13-Garbage_Collection_Cycle_Bucketing\137-Bucketing_to_eliminate_the_shuffle.mkv"178,027,822036B31BB
"14-Spark_Structured_Streaming\139-Evolution_of_Streaming_in_Spark.mkv"166,677,247DD782CFF
"14-Spark_Structured_Streaming\140-Programing_model_of_Structured_Streaming.mkv"231,054,83584CBC09A
"14-Spark_Structured_Streaming\143-The_technical_side_of_Stateful_Transformation.mkv"156,439,2696E5AE5FA
"14-Spark_Structured_Streaming\144-Checkpoint_Director_Backbone_for_idempotency.mkv"137,498,387A180BC89
"14-Spark_Structured_Streaming\146-Apply_Append_Mode_in_PySpark_Structured_Streaming.mkv"369,756,50283B162B3
"14-Spark_Structured_Streaming\149-Apply_Complete_Output_Mode.mkv"200,344,694B4FC5678
"14-Spark_Structured_Streaming\150-Trigger_Types_For_Structured_Streaming.mkv"199,604,3589A2323DF
"14-Spark_Structured_Streaming\151-Archive_Source_Files_In_Streaming.mkv"153,234,9933556B34B
"14-Spark_Structured_Streaming\152-ForEachBatch_Operation_For_Custom_Code.mkv"210,428,63583693973
"14-Spark_Structured_Streaming\155-Tumbling_Window_Operation.mkv"167,615,4086E3924D3
"14-Spark_Structured_Streaming\158-Integrate_Window_Operations_in_Streaming_Code.mkv"263,535,197AC0BAB7C
"14-Spark_Structured_Streaming\160-Watermarks_For_Spark_Structured_Streaming.mkv"152,601,843B55A67F0
"15-Spark_Connect_In_Apache_Spark\162-What_is_Spark_Connect.mkv"219,804,615C82EF77C
"15-Spark_Connect_In_Apache_Spark\163-Create_a_Spark_Connect_Object.mkv"101,572,03528A212B3
"16-Pandas_API_on_Apache_Spark\165-What_is_Pandas_API.mkv"162,082,002CF651269
"16-Pandas_API_on_Apache_Spark\166-How_to_work_with_Pandas_API_inside_Spark.mkv"182,197,395E801BC14
"16-Pandas_API_on_Apache_Spark\167-Pandas_User_Defined_Functions_UDFs.mkv"260,543,75327153881
"16-Pandas_API_on_Apache_Spark\168-Series_To_Series_UDFs.mkv"258,679,4638BC2CA52
"16-Pandas_API_on_Apache_Spark\169-Iterator_Series_To_Iterator_Series_UDFs.mkv"131,276,370919AF442
"16-Pandas_API_on_Apache_Spark\171-Series_To_Scalar_UDFs.mkv"160,931,829AB6F2B74
"17-Delta_Optimization_Techniques\172-How_to_Optimize_the_small_files.mkv"104,272,113B989CCA7
"17-Delta_Optimization_Techniques\174-Liquid_Clustering.mkv"132,242,868C2A1FF66
🔗 Chaîne de versions (2 variantes)
⭐ Meilleure version : UDEMY.Databricks.Certified.Associate.Developer.for.Apache.Sp...
Type Release Priorité Date
📦 Original ⭐ UDEMY.Databricks.Certified.Associate.Developer.for.Apache.Spark.4.2026.BOOKWARE-MiMiR 0 2026-06-08
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