Create sql.md

Author: propelledanalytics

docs/sql.md

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+# sql Function
+Submits *Structured Query Language* (SQL), *Data Manipulation Language* (DML) and *Data Definition Language* (DDL) statements to Apache Spark.
+
+# Arguments
+- `session:SparkSession`: the SparkSession.  See SparkSession help for instructions on how to create in Julia.
+- `sqlText::String`: the DDL, DML or SQL statements.
+
+# DDL Supported formats:
+- File formats including: CSV, JSON, arrow, parquet
+- Data Lakes including: Hive, ORC, Avro
+- Data Lake Houses: Delta Lake, Apache Iceberg.
+- Cloud Object Stores: S3, Azure Blob Storage, Swift Object.
+
+# Examples
+
+## CSV file example:
+Comma Separated Value (CSV) format.
+```
+stmt = sql(session, "SELECT * FROM CSV.`/pathToFile/fileName.csv`;")
+```
+## Parquet file example:
+Apache Parquet format.
+```
+stmt = sql(session, "SELECT * FROM PARQUET.`/pathToFile/fileName.parquet`;")
+```
+## Delta Lake Example:
+Delta Lake is an open-source storage layer for Spark. Delta Lake offers:
+
+ACID transactions on Spark: Serializable isolation levels ensure that readers never see inconsistent data.
+Scalable metadata handling: Leverages Spark’s distributed processing power to handle all the metadata for petabyte-scale tables with billions of files at ease.
+
+To use Delta Lake you must add the Delta Lake jar to your Spark jars folder.
+
+Example shows create table (DDL), insert (DML) and select statements (SQL) using Delta Lake and SparkSQL:
+```
+sql(session, "CREATE DATABASE demo;")
+sql(session, "USE demo;")
+sql(session, "CREATE TABLE tb(col STRING) USING DELTA;" )
+```