Apache Spark SQL
Apache Spark 2.2
| Intermediate
- 16 Videos | 1h 7m 32s
- Includes Assessment
- Earns a Badge
Apache Spark SQL is used for structured data processing in Spark. Explore features of Spark SQL such as SparkSessions, DataFrames, and Datasets.
WHAT YOU WILL LEARN
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describe Apache Spark SQL
create a SparkSession
create DataFrames with Spark SQL
use aggregations with the built-in DataFrames functions
run SQL queries programmatically
create a global temporary view
create Datasets with Spark SQL
use JSON Datasets with Spark SQL -
use Load/Save functions
manually specify a data source
run SQL directly on files
use SaveMode to handle save operations
write parquet files with Spark SQL
use Spark SQL to save a DataFrame as a persistent table
use partitioning when saving persistent tables
use Spark SQL to create Datasets and DataFrames
IN THIS COURSE
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1.Apache Spark SQL Overview2m 56sUP NEXT
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2.SparkSession3m 37s
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3.DataFrames4m 44s
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4.Aggregations4m 9s
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5.SQL Queries5m 10s
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6.Temporary View3m 41s
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7.Datasets2m 58s
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8.JSON Datasets4m 50s
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9.Load/Save Functions4m
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10.Specifying a Data Source4m 23s
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11.Querying with SQL3m 41s
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12.SaveMode3m 26s
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13.Parquet Files4m 5s
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14.Persistent Tables2m 37s
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15.Partitioning3m 4s
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16.Exercise: Use Spark SQL2m 44s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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