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SPARK - LRBA 2

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SPARK - LRBA 2

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Spark Core - Fundamentos y funcionalidades básicas

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HR Mexico
HR Mexico
Mexico

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SPARK - LRBA 2
 

SPARK - LRBA 2Online version

Spark Core - Fundamentos y funcionalidades básicas

by HR Mexico
1

¿Cuál es la diferencia principal entre transformaciones y acciones en RDDs?

2

¿Qué mecanismo usa Spark Core para tolerancia a fallos en RDDs?

3

¿Qué persistencia es óptima para datasets grandes con memoria limitada?

4

¿Qué operación causa shuffle obligatoriamente?

5

¿Cuál es el particionador default para reduceByKey?

6

¿Para qué sirve broadcast variable?

7

¿Qué config optimiza shuffle spills?

8

Pregunta 8 ¿Qué es un narrow dependency?

9

¿Cuándo usar checkpoint sobre persist?

10

Qué serializador es default en Spark 3+?

11

¿Qué scheduler divide DAG en stages?

12

¿Cuál locality es prioritaria?

13

Para qué sirve spark.sql.shuffle.partitions?

14

Pregunta 14 Qué mitiga stragglers?

15

Cuál es ventaja de Tungsten?

16

En qué modo driver corre en executor?

17

Qué usa acumulador?

18

Qué reduce skew en groupByKey?

19

Qué habilita dynamicAllocation?

20

Dónde monitorear storage levels?

Explicación

Transformaciones construyen DAG lazy; acciones evalúan y retornan valores/scalars.

Lineage reconstruye particiones perdidas recomputando dependientes.

Spill a disco previene OOM, balancea velocidad y resiliencia.

reduceByKey es wide dependency, requiere exchange por key.

HashPartitioner usa hash(key) % numPartitions.

Evita envío repetido en tasks, eficiente <100MB.

Buffer mayor reduce I/O en spills intermedios.

Permite pipelining sin shuffle (e.g., map).

Trunca lineage costoso en fallos raros pero profundos.

Kryo ofrece compresión y velocidad 10x vs. Java.

Identifica shuffle boundaries como breakpoints.

Maximiza data reuse minimizando red.

Default 200; ajustar 2-3x cores totales.

Duplica tasks lentos si >75% peers terminan.

Evita JVM GC con columnar off-heap.

Cluster mode aísla driver en clúster.

Operaciones commutativas thread-safe.

key + "_" + random() balancea partitions.

Escala executors basado en demanda.

Muestra RDDs persistidos y memoria usada.

 
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