Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

during start and stop. System-side Deployment When applying HA to Kyuubi deployment, we need to be aware of the below two thing basically, • kyuubi.ha.zookeeper.quorum - the external zookeeper cluster address Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin

during start and stop. System-side Deployment When applying HA to Kyuubi deployment, we need to be aware of the below two thing basically, • kyuubi.ha.zookeeper.quorum - the external zookeeper cluster address Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin

during start and stop. System-side Deployment When applying HA to Kyuubi deployment, we need to be aware of the below two thing basically, • kyuubi.ha.zookeeper.quorum - the external zookeeper cluster address Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin

Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin scenarios. End-users can focus on developing their business systems and mining data value without being aware of the underlying big data platform (compute engines, storage services, metadata management, etc.)

Kyuubi, Release 1.7.0 System-side Deployment When applying HA to Kyuubi deployment, we need to be aware of the below two thing basically, • kyuubi.ha.zookeeper.quorum - the external zookeeper cluster address Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.advisoryPartitionSizeInBytes=128m spark.sql.adaptive.coalescePartitions Tips for Best Practises For further tuning our Spark jobs with this feature, we also need to be aware of these configs. spark.sql.adaptive.skewJoin.skewedPartitionFactor=5 spark.sql.adaptive.skewJoin