Databricks Community

If you're looking to partition your `target_path` table, then it's recommended to define the partition keys prior to the COPY INTO command (at the DDL level)E.g.// Drop table if it already exists without the partition key defined (OPTIONNAL) DROP TAB...

As indicated there are ways to manage the amount of data being sampled for inferring schema. However as a best practice for production workloads its always best to define the schema explicitly for consistency, repeatability and robustness of the pipe...

@peyman what if I don't want to manually specify the schema? For example, I have a vendor that can't build a valid .csv file. I just need to import it somewhere so I can explore the data and find the errors. Just like the original author's question?...

Create temp folder inside output folder. Copy file part-00000* with the file name to output folder. Delete the temp folder. Python code snippet to do the same. fpath=output+'/'+'temp' def file_exists(path): try: dbutils.fs.ls(path) return...

Take a look here for options, http://spark.apache.org/docs/latest/api/python/pyspark.sql.html?highlight=dataframereader#pyspark.sql.DataFrameReader.csv If a csv file has commas then the tradition is to quote the string that contains the comma, In ...

This is apparently a known issue, databricks has their own csv format handler which can handle this https://github.com/databricks/spark-csv SQL API CSV data source for Spark can infer data types: CREATE TABLE cars USING com.databricks.spark.csv OP...

# in python: explicitly define the schema, read in CSV data using the schema and a defined timestamp format.... <a href="http://thestoreguide.co.nz/auckland/orewa/mcdonalds-orewa-akl-0931/">McDonald’s in Orewa</a>

You can also always read in the file as a textFile, and then run a UTF-16 decoder/encoder library as a UDF on the text.

Do quote or escape options only work with "Write" instead of "read"? Our source files contain doube quotes. We'd like to add backsplash (escape) in front each double quote before converting the values from out dataframes to json outputs.