Apache Spark を使用して、OCR を使用して画像から抽出されたテキストを効率的に文字列照合および検証するにはどうすればよいですか?

<code class="scala">import org.apache.spark.ml.feature.{RegexTokenizer, NGram, HashingTF, MinHashLSH, MinHashLSHModel}

// Input text
val query = Seq("Hello there 7l | real|y like Spark!").toDF("text")

// Reference data
val db = Seq(
  "Hello there ?! I really like Spark ❤️!", 
  "Can anyone suggest an efficient algorithm"
).toDF("text")

// Create pipeline
val pipeline = new Pipeline().setStages(Array(
  new RegexTokenizer().setPattern("").setInputCol("text").setMinTokenLength(1).setOutputCol("tokens"),
  new NGram().setN(3).setInputCol("tokens").setOutputCol("ngrams"),
  new HashingTF().setInputCol("ngrams").setOutputCol("vectors"),
  new MinHashLSH().setInputCol("vectors").setOutputCol("lsh")
))

// Fit on reference data
val model = pipeline.fit(db)

// Transform both input text and reference data
val db_hashed = model.transform(db)
val query_hashed = model.transform(query)

// Approximate similarity join
model.stages.last.asInstanceOf[MinHashLSHModel]
  .approxSimilarityJoin(db_hashed, query_hashed, 0.75).show</code>