Clone Drone In The Danger Zone V0.9.0.25 Dna Hack
Clone Drone In The Danger Zone V0.9.0.25 Dna Hack
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Josef Groh (born 7 April 1952) is a Swiss former swimmer. He competed in the 200 m and 4 × 100 m freestyle events at the 1968 Summer Olympics and the 1972 Summer Olympics. In addition to his own swimming career, Groh has also worked for UBS as a financial analyst.
References
Category:1952 births
Category:Living people
Category:Swiss male swimmers
Category:Olympic swimmers of Switzerland
Category:Swimmers at the 1968 Summer Olympics
Category:Swimmers at the 1972 Summer Olympics
Category:Universiade medalists in swimming
Category:Universiade gold medalists for Switzerland
Category:Place of birth missing (living people)
struct _pthread_attr_t {
unsigned int __pad1;
unsigned int __pad2;
unsigned int __pad3;
};
struct _pthread_cleanup_buffer {
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};
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unsigned int __pad1;
unsigned int __pad2;
unsigned int __pad3;
};
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unsigned int __pad1;
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How to partition a large database in Spark
For a very large database on Spark (1 Terabyte in our case), we want to split it into 2 partitions. We don’t know exactly the partitions, but know that we want them to be roughly equal in size.
How to partition the dataset while using the Spark API? Is there a API that can serve this purpose?
A:
You can use the spark.sql.script option to write a table schema to a file in text format. This can be used to partition the data on the fly. E.g.
spark.sql(“CREATE TABLE myTable(column1 STRING, column2 STRING) PARTITIONED BY (partitionCol BIGINT)”)
CREATE TABLE myTable(column1 STRING, column2 STRING) PARTITIONED BY (partitionCol BIGINT)
You can use Spark SQL to read the script and create a table.
A good blog post with examples on using spark.sql.script
A:
Scala version:
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.TableIdentifier
val sqlContext =
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