Ben Chuanlong Du's Blog

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Process Big Data Using PySpark

  1. PySpark 2.4 and older does not support Python 3.8. You have to use Python 3.7 with PySpark 2.4 or older.

  2. It can be extremely helpful to run a PySpark application locally to detect possible issues before submitting it to the Spark cluster.

    #!/usr/bin/env bash …

User-defined Function (UDF) in PySpark

Tips and Traps

  1. The easist way to define a UDF in PySpark is to use the @udf tag, and similarly the easist way to define a Pandas UDF in PySpark is to use the @pandas_udf tag. Pandas UDFs are preferred to UDFs for server reasons. First, pandas UDFs are typically much faster than UDFs. Second, pandas UDFs are more flexible than UDFs on parameter passing. Both UDFs and pandas UDFs can take multiple columns as parameters. In addition, pandas UDFs can take a DataFrame as parameter (when passed to the apply

Regular Expression Equivalent

  1. The order of precedence of operators in POSIX extended regular expression is as follows.

    1. Collation-related bracket symbols [==], [::], [..]
    2. Escaped characters \
    3. Character set (bracket expression) []
    4. Grouping ()
    5. Single-character-ERE duplication *, +, ?, {m,n}
    6. Concatenation
    7. Anchoring ^, $
    8. Alternation |

  2. Some regular expression patterns are defined using a single leading backslash, e.g., \s, \b, etc. However, since special …