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SPARK - LRBA 12

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SPARK - LRBA 12

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Buenas practicas LRBA

Created by

HR Mexico
HR Mexico
Mexico

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SPARK - LRBA 12
 

SPARK - LRBA 12Online version

Buenas practicas LRBA

by HR Mexico
1

¿Cuál es el modo de despliegue principal en LRBA para minimizar latencia driver?

2

¿Qué configuración desactiva en LRBA para predictibilidad batch?

3

En LRBA, ¿qué porcentaje aproximado del executor-memory se asigna a unified regions?

4

¿Cuál es el tamaño target de partición post-shuffle en LRBA?

5

¿Qué métrica debe ser <5% en Spark UI para LRBA óptimo?

6

En skew handling LRBA, ¿qué técnica usa random suffix?

7

¿Qué JVM option reduce GC pauses en LRBA?

8

En Kubernetes LRBA, ¿qué limita cores por executor?

9

¿Qué scheduler mode usa LRBA por default?

10

¿Qué servicio descarga shuffle del executor local en YARN LRBA?

11

¿Para qué se usa rdd.checkpoint() en LRBA?

12

¿Cuál es el speedup típico LRBA vs estándar en TPC-DS?

13

¿Qué config habilita memoria fuera heap?

14

En LRBA, ¿cuántos cores reservar por nodo para OS?

15

¿Qué feature dinamiza partitions en AQE LRBA?

16

¿Cuál heartbeat interval recomienda LRBA?

17

En caso BBVA-like, ¿cuánto redujo LRBA el tiempo ETL?

18

¿Qué evita duplicar tasks en batch LRBA?

19

¿Métrica GC target en LRBA?

20

En retail caso, ¿qué optimizó aggregations en LRBA?

Explicación

Client mode posiciona driver localmente, reduciendo serialización red.

Dynamic allocation causa churn; LRBA usa pools fijos.

spark.memory.fraction=0.8 por default en Spark 3.x.

Óptimo para balance memoria/disk I/O.

Spill indica memoria insuficiente.

Salting distribuye keys skewed uniformemente.

G1GC low-latency para workloads Spark.

Ambas configs aseguran límites pods.

FIFO prioriza locality en batch.

Reduce overhead local storage.

Materializa lineage costoso.

Benchmarks confirman 50-100% mejora.

Delega a native memory.

Evita saturación daemons.

Post-shuffle coalescing.

Balance responsiveness/overhead.

De 4h a 1.5h en 50TB.

Speculation innecesario en determinísticos.

>10% indica tuning necesario.

Combo redujo GC y memoria uso.

 
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