Efficient String Matching with Apache Spark: A Comprehensive Guide
Introduction:
The increasing use of Optical Character Recognition (OCR) tools has highlighted the need for efficient string matching algorithms to handle OCR errors. Spark, a popular data processing framework, offers a range of solutions for this task.
Problem:
When performing OCR on screenshots, errors such as letter substitutions ("I" and "l" to "|"), emoji replacement, and space removal can occur. Matching these extracted texts against a large dataset poses a challenge due to these inaccuracies.
Solution:
Spark provides a combination of machine learning transformers that can be combined to perform efficient string matching.
Steps:
<code class="scala">import org.apache.spark.ml.feature.RegexTokenizer val tokenizer = new RegexTokenizer().setPattern("").setInputCol("text").setMinTokenLength(1).setOutputCol("tokens")</code>
<code class="scala">import org.apache.spark.ml.feature.NGram val ngram = new NGram().setN(3).setInputCol("tokens").setOutputCol("ngrams")</code>
<code class="scala">import org.apache.spark.ml.feature.HashingTF val vectorizer = new HashingTF().setInputCol("ngrams").setOutputCol("vectors")</code>
<code class="scala">import org.apache.spark.ml.feature.{MinHashLSH, MinHashLSHModel} val lsh = new MinHashLSH().setInputCol("vectors").setOutputCol("lsh")</code>
<code class="scala">import org.apache.spark.ml.Pipeline val pipeline = new Pipeline().setStages(Array(tokenizer, ngram, vectorizer, lsh))</code>
<code class="scala">val query = Seq("Hello there 7l | real|y like Spark!").toDF("text") val db = Seq( "Hello there ?! I really like Spark ❤️!", "Can anyone suggest an efficient algorithm" ).toDF("text") val model = pipeline.fit(db)</code>
<code class="scala">val dbHashed = model.transform(db) val queryHashed = model.transform(query) model.stages.last.asInstanceOf[MinHashLSHModel] .approxSimilarityJoin(dbHashed, queryHashed, 0.75).show</code>
This approach allows for efficient string matching despite the OCR errors, resulting in accurate results.
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