Hi folks, Any solution to it? PFB.
Thanks, Aakash. ---------- Forwarded message ---------- From: Aakash Basu <aakash.spark....@gmail.com> Date: Tue, Sep 19, 2017 at 2:32 PM Subject: Help needed in Dividing open close dates column into multiple columns in dataframe To: user <user@spark.apache.org> Hi, I've a csv dataset which has a column with all the details of store open and close timings as per dates, but the data is highly variant, as follows - Mon-Fri 10am-9pm, Sat 10am-8pm, Sun 12pm-6pm Mon-Sat 10am-8pm, Sun Closed Mon-Sat 10am-8pm, Sun 10am-6pm Mon-Friday 9-8 / Saturday 10-7 / Sunday 11-5 Mon-Sat 9am-8pm, Sun 10am-7pm Mon-Sat 10am-8pm, 11am - 6pm Mon-Fri 9am-6pm, Sat 10am-5pm, Sun Closed Mon-Thur 10am-7pm, Fri 10am-5pm, Sat Closed, Sun 10am-5pm Mon-Sat 10-7 Sun Closed MON-FRI 10:00-8:00, SAT 10:00-7:00, SUN 12:00-5:00 I have to split the data of this one column into 14 columns, as - Monday Open Time Monday Close Time Tuesday Open Time Tuesday Close Time Wednesday Open Time Wednesday Close Time Thursday Open Time Thursday Close Time Friday Open Time Friday Close Time Saturday Open Time Saturday Close Time Sunday Open Time Sunday Close Time Can someone please let me know if someone faced similar issue and also how they resolved this in SparkSQL dataframes. Using: CSV data, Spark 2.1, PySpark, using dataframes. (Tried using case statement.) Thanks, Aakash.
