Love da lo lolli

[vendettaa]

1 minute ago, tacobell fan said:

ee DB lo antha Hadoop lolli evadiki ledu. Unna they know where to discuss. Sync avvatledu. Moreover chinna question ki nuvvu paragraph post chestunte inka ekkuva doubt ga undi. Just check this 

 

 

 

sarle edokati anuko i dont mind

nenipdu elago interviews ki prep avtunna , e post chudagane post chesa , prep avtu dbing 

[vendettaa]

3 minutes ago, MuPaGuNa said:

chi deenamma jeevitham...

deeni self dabba thagaleyya...evadanna oka sepraasi post anna ippinchandi vaa...

ee chendalam soodalekapothunna naa love da lo di

same to u , ni mohaniki elago radu , raka na mida yedustunav

adigindaniki chepte kuda nee yedupe

nenaite ilanti questions db lo adaga, i discuss with my collegues 

coding doubts unte adguta adi worst case lo , i even got help from db , there are ids who helped me  5 months back data pipeline design matter lo

inka worst case lo stack over flow lo adguta 

i encourage people who try to learn , ni lanti valani chuste papam anpistadi ante 

[ThedaSingh]

5 minutes ago, tacobell fan said:

ee DB lo antha Hadoop lolli evadiki ledu. Unna they know where to discuss. Sync avvatledu. Moreover chinna question ki nuvvu paragraph post chestunte inka ekkuva doubt ga undi. Just check this 

 

 

 

arey.. TableFan endhi nee lolli.. teliste cheppu lekunte news articles vesko.. 

[tacobell fan]

Just now, ThedaSingh said:

arey.. TableFan endhi nee lolli.. teliste cheppu lekunte news articles vesko.. 

[MuPaGuNa]

1 minute ago, vendettaa said:

same to u , ni mohaniki elago radu , raka na mida yedustunav

adigindaniki chepte kuda nee yedupe

nenaite ilanti questions db lo adaga, i discuss with my collegues 

coding doubts unte adguta adi worst case lo , i even got help from db , there are ids who helped me 

inka worst case lo stack over flow lo adguta 

i encourage people who try to learn , ni lanti valani chuste papam anpistadi ante 

vooko vanty nee lolli db mottam telusu..nuvvu nee veshalu...

oh pee tee meeda 3 yrs lo 2.6 months bench meeda vunna record naade vanty ....that credit goes to me only...

em chesthm edo ala brathukutunna...

 

 

[ThedaSingh]

Just now, tacobell fan said:

[vendettaa]

15 minutes ago, ThedaSingh said:

aak paak annattun undi idhi.. google lo dorakatle.

i want exact definition.. dorikite veyyandi ikkada.

ok DAG is something internal, its a algorithm runs backend when u run on hadoop  especially processing using spark or tez, graph lo elaga edges vertex concept untadi  alage vertex is something data and if u apply any computation on it that is edge  ,idanta backend nadustadi 

like x=2 here x is vertex 

x^2 like here ur transforming x  ,this process is edge 

ide concept , ardam kakapote inka nenem cheppalenu

[vendettaa]

13 minutes ago, ThedaSingh said:

arey.. TableFan endhi nee lolli.. teliste cheppu lekunte news articles vesko.. 

i tried to explain you, ardam kakapote nenem cheylenu, i dont want to discuss here, endo janalu aa insecurity thinking vignana pradarshana shardam antunnaru 

[ekunadam_enkanna]

endi va. Before the hadoop business and vagaira, people worried about responsiveness, how to share a single core processor among multiple processes, etc. That's the discussion of concurrency, critical section, dead locks, etc. That's where this vertex lolli started. They used to call resource graphs or something like that (open an OS text book). Imagine you want to compute the sum of the first 3M natural numbers, and you have 16 cores. How do you achieve it? You can draw a graph like: start --> {P1,  P2, P3, P4, ...,P16} --> end (or join). This is a graph, and it has direction ( -->). if there are no cycles, you can show that there are no deadlocks--hence acyclic. You have this DAG business here. Extend this sh1t from unicore processor to 1000 machines, etc. This map-reduce business is just an extension of the old school currency on a unicore processor with bells and whistles, and other distributed computation problems.

 

[ThedaSingh]

14 minutes ago, vendettaa said:

i tried to explain you, ardam kakapote nenem cheylenu, i dont want to discuss here, endo janalu aa insecurity thinking vignana pradarshana shardam antunnaru 

ippudu ninnu emanna mahaprabho??

[vendettaa]

TS ki thanks malli 

e thread vesinanduku revision cheskunna concepts

[ThedaSingh]

2 minutes ago, ekunadam_enkanna said:

endi va. Before the hadoop business and vagaira, people worried about responsiveness, how to share a single core processor among multiple processes, etc. That's the discussion of concurrency, critical section, dead locks, etc. That's where this vertex lolli started. They used to call resource graphs or something like that (open an OS text book). Imagine you want to compute the sum of the first 3M natural numbers, and you have 16 cores. How do you achieve it? You can draw a graph like: start --> {P1,  P2, P3, P4, ...,P16} --> end (or join). This is a graph, and it has direction ( -->). if there are no cycles, you can show that there are no deadlocks--hence acyclic. You have this DAG business here. Extend this sh1t from unicore processor to 1000 machines, etc. This map-reduce business is just an extension of the old school currency on a unicore processor with bells and whistles, and other distributed computation problems.

 

[tacobell fan]

6 minutes ago, ekunadam_enkanna said:

endi va. Before the hadoop business and vagaira, people worried about responsiveness, how to share a single core processor among multiple processes, etc. That's the discussion of concurrency, critical section, dead locks, etc. That's where this vertex lolli started. They used to call resource graphs or something like that (open an OS text book). Imagine you want to compute the sum of the first 3M natural numbers, and you have 16 cores. How do you achieve it? You can draw a graph like: start --> {P1,  P2, P3, P4, ...,P16} --> end (or join). This is a graph, and it has direction ( -->). if there are no cycles, you can show that there are no deadlocks--hence acyclic. You have this DAG business here. Extend this sh1t from unicore processor to 1000 machines, etc. This map-reduce business is just an extension of the old school currency on a unicore processor with bells and whistles, and other distributed computation problems.

ee sollu architecture motham Abinitio ani ETL tool lo jamana lo undi with multi file system ani parallel processing by using computing power from multi node, but Hadoop ani Peru petti open source chesi commodity hardware tho hadavudi chestunnaru. Oka rule ledu, oka data governance process ledu with Big Data, company lo evadu padithe Vadu hadoop antaru, head edo tail edo kuda teliyadhu. Meaning no one has any clue wihat other team is going to use Hadoop for, so blind ga Hadoop team anni technology stacks ni ela support chestaru to ingest the data and play by the organization compliance rules.

[ThedaSingh]

Just now, tacobell fan said:

ee sollu architecture motham Abinitio ani ETL tool lo jamana lo undi with multi file system ani parallel processing by using computing power from multi node, but Hadoop ani Peru petti open source chesi commodity hardware tho hadavudi chestunnaru. Oka rule ledu, oka data governance process ledu with Big Data, company lo evadu padithe Vadu hadoop antaru, head edo tail edo kuda teliyadhu. Meaning no one has any clue with other team is going to use Hadoop for, so blind ga Hadoop team anni technology stacks ni ela support chestaru to ingest the data and play by the organization compliance rules.

neeku jealous e 

 

[tacobell fan]

Just now, ThedaSingh said:

neeku jealous e 

Matter ardham aithe neeku pichukulu egurutayi, appati varuku you don't even understand a thing.