Best way to get the max value in a Spark dataframe column

Question

I\'m trying to figure out the best way to get the largest value in a Spark dataframe column.

Consider the following example:

df = spark.createDataFra         


        

Answer 1

Another way of doing it:

df.select(f.max(f.col("A")).alias("MAX")).limit(1).collect()[0].MAX

On my data, I got this benchmarks:

df.select(f.max(f.col("A")).alias("MAX")).limit(1).collect()[0].MAX
CPU times: user 2.31 ms, sys: 3.31 ms, total: 5.62 ms
Wall time: 3.7 s

df.select("A").rdd.max()[0]
CPU times: user 23.2 ms, sys: 13.9 ms, total: 37.1 ms
Wall time: 10.3 s

df.agg({"A": "max"}).collect()[0][0]
CPU times: user 0 ns, sys: 4.77 ms, total: 4.77 ms
Wall time: 3.75 s

All of them give the same answer