[MINOR][DOCS] Use ASCII characters when possible in PySpark documentation
### What changes were proposed in this pull request? This PR replaces the non-ASCII characters to ASCII characters when possible in PySpark documentation ### Why are the changes needed? To avoid unnecessarily using other non-ASCII characters which could lead to the issue such as https://github.com/apache/spark/pull/32047 or https://github.com/apache/spark/pull/22782 ### Does this PR introduce _any_ user-facing change? Virtually no. ### How was this patch tested? Found via (Mac OS): ```bash # In Spark root directory cd python pcregrep --color='auto' -n "[\x80-\xFF]" `git ls-files .` ``` Closes #32048 from HyukjinKwon/minor-fix. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: Max Gekk <max.gekk@gmail.com>
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@ -42,7 +42,7 @@ SQL query engine.
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Running on top of Spark, the streaming feature in Apache Spark enables powerful
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interactive and analytical applications across both streaming and historical data,
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while inheriting Spark’s ease of use and fault tolerance characteristics.
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while inheriting Spark's ease of use and fault tolerance characteristics.
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**MLlib**
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@ -22,7 +22,7 @@ Upgrading from PySpark 2.4 to 3.0
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* In Spark 3.0, PySpark requires a pandas version of 0.23.2 or higher to use pandas related functionality, such as ``toPandas``, ``createDataFrame`` from pandas DataFrame, and so on.
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* In Spark 3.0, PySpark requires a PyArrow version of 0.12.1 or higher to use PyArrow related functionality, such as ``pandas_udf``, ``toPandas`` and ``createDataFrame`` with “spark.sql.execution.arrow.enabled=true”, etc.
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* In Spark 3.0, PySpark requires a PyArrow version of 0.12.1 or higher to use PyArrow related functionality, such as ``pandas_udf``, ``toPandas`` and ``createDataFrame`` with "spark.sql.execution.arrow.enabled=true", etc.
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* In PySpark, when creating a ``SparkSession`` with ``SparkSession.builder.getOrCreate()``, if there is an existing ``SparkContext``, the builder was trying to update the ``SparkConf`` of the existing ``SparkContext`` with configurations specified to the builder, but the ``SparkContext`` is shared by all ``SparkSession`` s, so we should not update them. In 3.0, the builder comes to not update the configurations. This is the same behavior as Java/Scala API in 2.3 and above. If you want to update them, you need to update them prior to creating a ``SparkSession``.
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@ -107,7 +107,7 @@ In the case of a ``spark-submit`` script, you can use it as follows:
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Note that ``PYSPARK_DRIVER_PYTHON`` above should not be set for cluster modes in YARN or Kubernetes.
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If you’re on a regular Python shell or notebook, you can try it as shown below:
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If you're on a regular Python shell or notebook, you can try it as shown below:
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.. code-block:: python
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@ -161,11 +161,11 @@ class FPGrowth(JavaEstimator, _FPGrowthParams, JavaMLWritable, JavaMLReadable):
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.. [1] Haoyuan Li, Yi Wang, Dong Zhang, Ming Zhang, and Edward Y. Chang. 2008.
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Pfp: parallel fp-growth for query recommendation.
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In Proceedings of the 2008 ACM conference on Recommender systems (RecSys '08).
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Association for Computing Machinery, New York, NY, USA, 107–114.
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Association for Computing Machinery, New York, NY, USA, 107-114.
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DOI: https://doi.org/10.1145/1454008.1454027
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.. [2] Jiawei Han, Jian Pei, and Yiwen Yin. 2000.
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Mining frequent patterns without candidate generation.
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SIGMOD Rec. 29, 2 (June 2000), 1–12.
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SIGMOD Rec. 29, 2 (June 2000), 1-12.
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DOI: https://doi.org/10.1145/335191.335372
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@ -143,7 +143,7 @@ class BisectingKMeans(object):
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-----
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See the original paper [1]_
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.. [1] Steinbach, M. et al. “A Comparison of Document Clustering Techniques.” (2000).
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.. [1] Steinbach, M. et al. "A Comparison of Document Clustering Techniques." (2000).
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KDD Workshop on Text Mining, 2000
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http://glaros.dtc.umn.edu/gkhome/fetch/papers/docclusterKDDTMW00.pdf
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"""
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