High-Throughput Vector Ingestion & Hybrid Search
Power enterprise RAG applications with real-time neural data lakes. We engineer high-throughput data pipelines using AWS Glue PySpark jobs, S3 Iceberg, serverless Lambda embedders, and OpenSearch hybrid vector search indices.
Production-tested execution flow designed for multi-region reliability and security.
Streams document updates and database change logs via Kinesis to S3.
Executes serverless PySpark ETL to chunk text and format into Snappy Parquet.
Generates dense vector embeddings using foundation embedding models.
Updates BM25 lexical + dense k-NN vector search indices for sub-50ms RAG queries.
Scales automatically to process millions of unstructured enterprise documents and log streams.
Combines traditional BM25 keyword search with dense k-NN vector embeddings for high retrieval accuracy.
Ingests document edits via AWS Kinesis and Lambda embedders so RAG stores stay continuously updated.
Stores raw and processed corpora in open columnar formats with compression and temporal versioning.
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from pyspark.sql.functions import col
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
# Load raw enterprise data from S3
df = spark.read.json("s3://enterprise-lake/documents/*.json")
cleaned_df = df.filter(col("text").isNotNull()).select("doc_id", "title", "text")
# Write to columnar Snappy Parquet
cleaned_df.write.mode("overwrite").parquet("s3://enterprise-lake/processed-parquet/")
print("✓ AWS Glue Data Pipeline Transformation Completed Successfully.")Pure vector search can miss exact alphanumeric strings like part numbers or customer IDs. Hybrid search merges BM25 keyword precision with semantic vector context.
AWS Glue runs PySpark jobs serverlessly, automatically allocating worker nodes based on dataset volume to process terabytes of data quickly.
Book an architecture review session with our senior AI engineers to assess your infrastructure and custom requirements.
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