Jules S Damji – författare

In his stunning debut of stories, Jules S. Damji explores the social ethos of an immigrant Asian community set in the early 1960s through to the 1970s, a decade of immense political changes that marked many peoples lives in Dar es Salaam, Tanzania.

Starting with Mango Tree, a metaphor of stability which embodies a center around which a community revolves, only to be seen destroyed and a way of life lost; Caretaker tenderly reveals the hidden and wretched historical past of a man dedicated to service his community; the nefarious characters in Middlemen are a poignant reminder of human flaws: graft, greed, manipulation, lust, and power; family relationships in Marxist and His Sister and A Household Divided wickedly and woefully capture the predicament universally endured by so many when an ideology is embraced to the point of fault; Oyster Bay and Freedom Fighter is a cry for breaking away and a genesis of a writer; and ending with Family Reunion, a glimpse into the narrators desire to illuminate his fading past.

Sometimes with strokes of simple and lucid prose that tugs your heart, other times with cool detachment and assured maturity that bucks your sensibility, Mr. Damji masterfully chronicles a slice of history through the tragically comic fictional characters set in Dar es Salaams residential district of Upanga, a setting intimately familiar to him.

Data is bigger, arrives faster, and comes in a variety of formatsâ??and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark.

Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, youâ??ll be able to:

Learn Python, SQL, Scala, or Java high-level Structured APIsUnderstand Spark operations and SQL EngineInspect, tune, and debug Spark operations with Spark configurations and Spark UIConnect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or KafkaPerform analytics on batch and streaming data using Structured StreamingBuild reliable data pipelines with open source Delta Lake and SparkDevelop machine learning pipelines with MLlib and productionize models using MLflow