Update API links. Fix Hive example.

docs/sql-programming-guide.md

@@ -38,8 +38,8 @@ file, or by running HiveQL against data stored in [Apache Hive](http://hive.apac
 
 Spark SQL allows relational queries expressed in SQL or HiveQL to be executed using
 Spark.  At the core of this component is a new type of RDD,
-[SchemaRDD]().  SchemaRDDs are composed
-[Row]() objects along with
+[SchemaRDD](api/pyspark/pyspark.rdd.SchemaRDD-class.html).  SchemaRDDs are composed
+[Row](api/pyspark/pyspark.rdd.Row-class.html) objects along with
 a schema that describes the data types of each column in the row.  A SchemaRDD is similar to a table
 in a traditional relational database.  A SchemaRDD can be created from an existing RDD, parquet
 file, or by running HiveQL against data stored in [Apache Hive](http://hive.apache.org/).
@@ -85,7 +85,7 @@ JavaSQLContext sqlCtx = new org.apache.spark.sql.api.java.JavaSQLContext(ctx);
 <div data-lang="python"  markdown="1">
 
 The entry point into all relational functionality in Spark is the
-[SQLContext]() class, or one
+[SQLContext](api/pyspark/pyspark.context.SQLContext-class.html) class, or one
 of its decedents.  To create a basic SQLContext, all you need is a SparkContext.
 
 {% highlight python %}
@@ -401,7 +401,7 @@ expressed in HiveQL.
 {% highlight python %}
 
 from pyspark.context import HiveContext
-hiveCtx = HiveContext(sqlCtx)
+hiveCtx = HiveContext(sc)
 
 hiveCtx.hql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING)")
 hiveCtx.hql("LOAD DATA LOCAL INPATH 'examples/src/main/resources/kv1.txt' INTO TABLE src")