running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190) at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)

Functions apsw, an advanced sqlite driver BerkeleyDB backend Sqlcipher backend Postgresql Extensions DataSet Django Integration Fields Generic foreign keys Hybrid Attributes Key/Value Store Shortcuts Signal backend Postgresql Extensions High-level features Fields Shortcuts Hybrid Attributes Signal support DataSet Key/Value Store Generic foreign keys CSV Utils Database management and framework integration pwiz # Note `to_tsvector()`. DataSet The dataset module contains a high-level API for working with databases modeled after the popular project of the same name [https://dataset.readthedocs.io/en/latest/index

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts ct(commands.scala:79) at org.apache.spark.sql.Dataset.$anonfun$logicalPlan$1(Dataset.scala:229) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618) at org.apache.spark.sql.execution

running Spark SQL queries. You do not need to set a proper shuffle partition number to fit your dataset. To enable this feature, we need to set the below two configs to true. spark.sql.adaptive.enabled=true oin=0.2 By default, if there are only less than 20% partitions of the dataset contain data, Spark will not broadcast the dataset. EliminateJoinToEmptyRelation This optimization rule detects and converts ct(commands.scala:79) at org.apache.spark.sql.Dataset.$anonfun$logicalPlan$1(Dataset.scala:229) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618) at org.apache.spark.sql.execution