In this document, the challenges and solutions for searching Chinese, Japanese, and Korean texts using Elasticsearch 6.2 are explored, focusing on the need for custom language analyzers. It highlights that the default analyzer, known as the standard analyzer, is not optimal for these languages due to their agglutinative nature and the use of complex scripts, which results in poor tokenization. The text provides examples of how the standard analyzer performs inadequately by combining nouns with postpositions in Korean and Japanese or breaking down Chinese characters into individual tokens. To address these issues, the document introduces language-specific analyzers such as kuromoji for Japanese, smartcn for Chinese, and openkoreantext-analyzer for Korean, which offer improved tokenization by correctly handling postpositions and maintaining the integrity of words and characters. These custom plugins need to be installed on every node in the Elasticsearch cluster to enhance search capabilities, and their effectiveness is demonstrated through examples with improved tokenization results.