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SPARK - LRBA 11

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SPARK - LRBA 11

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LRBA Properties

Created by

HR Mexico
HR Mexico
Mexico

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SPARK - LRBA 11
 

SPARK - LRBA 11Online version

LRBA Properties

by HR Mexico
1

¿Cuál es la principal reducción en payload por task en LRBA comparado con legacy Spark?

2

¿Qué configuración habilita coalescencia dinámica en LRBA?

3

En LRBA, ¿qué almacena UnsafeRow?

4

¿Cuál es el default de spark.sql.adaptive.advisoryPartitionSizeInBytes?

5

¿Qué activa Push-Based Shuffle en LRBA?

6

En speculative execution 2.0, ¿cuándo se replica un task?

7

¿Cuál es el beneficio principal de barrier execution en LRBA?

8

En caso BBVA, ¿cuánto se redujo tiempo ETL con LRBA?

9

¿Qué métrica alerta spill en LRBA?

10

¿Cuál es el pool de threads default en LRBA executors?

11

¿Qué evita LRBA en shuffles skewed?

12

En Telcel caso, ¿qué speedup en throughput?

13

¿Qué KryoRegistrator para SQL en LRBA?

14

¿Qué modelo usa LRBA para scaling?

15

¿Qué compresión usa LRBA shuffle?

16

¿Qué deshabilita UDFs en buenas prácticas LRBA?

17

En benchmarks TPC-H Q19, ¿speedup LRBA?

18

¿Qué habilita localShuffleReader?

19

¿Cuál es MTTR reducción con LRBA?

20

Requisito para Dynamic Filter Pushdown en LRBA?

Explicación

LRBA serializa solo metadata (<1 KB) vs closures completos (10-50 KB), factor 20-100x.

AQE (spark.sql.adaptive.enabled) activa coalescencia post-shuffle.

UnsafeRow es formato columnar off-heap para eficiencia memoria.

Target size para coalescencia es 64 MB por defecto.

Tungsten habilita push shuffle columnar con ZSTD.

Umbral probabilístico basado en estadísticas de stage.

Barriers livianos para joins sin global sync.

De 4h a 1.2h en 5 TB transacciones.

spillRatio >0.1 indica problemas off-heap.

spark.executor.threads=8 para concurrencia fija.

UnsafeExternalSorter reduce spill via columnar.

De 5 a 15 TB/h en logs CDR.

Optimiza serialización SQL objects.

Ajusta basados en utilization ρ.

ZSTD ratio 5:1 en columnar data.

Pandas UDF vectorizados evitan overhead.

1200s a 320s en 10 TB.

Optimiza shuffle intra-executor, max 4 executors.

Sub-DAG recompute acelera recovery.

Filtros broadcast pre-shuffle reducen data movida.

 
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