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perf(enriched_genes): UNIC-3037 Broadcast and agg smaller gene set dfs #234

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Aug 1, 2024
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perf(enriched_genes): UNIC-3037 Broadcast and agg smaller gene set dfs #234

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31 changes: 16 additions & 15 deletions datalake-spark3/src/main/scala/bio/ferlab/datalake/spark3/publictables/enriched/Genes.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,6 @@ package bio.ferlab.datalake.spark3.publictables.enriched
import bio.ferlab.datalake.commons.config.{Coalesce, DatasetConf, RuntimeETLContext}
import bio.ferlab.datalake.spark3.etl.v4.SimpleSingleETL
import bio.ferlab.datalake.spark3.implicits.DatasetConfImplicits._
import bio.ferlab.datalake.spark3.implicits.GenomicImplicits._
import bio.ferlab.datalake.spark3.implicits.GenomicImplicits.columns.locusColumnNames
import bio.ferlab.datalake.spark3.implicits.SparkUtils.removeEmptyObjectsIn
import bio.ferlab.datalake.spark3.publictables.enriched.Genes._
import mainargs.{ParserForMethods, main}
Expand Down Expand Up @@ -76,17 +74,18 @@ object Genes {

implicit class DataFrameOps(df: DataFrame) {

def joinAndMergeWith(gene_set: DataFrame,
joinOn: Seq[String],
asColumnName: String,
aggFirst: Boolean = false): DataFrame = {
def joinAndMergeWith(other: DataFrame,
joinOn: Seq[String],
asColumnName: String,
aggFirst: Boolean = false,
broadcastOtherDf: Boolean = false): DataFrame = {
val aggFn: Column => Column = c => if (aggFirst) first(c) else collect_list(c)
val aggDF = df
.join(gene_set, joinOn, "left")
.join(if (broadcastOtherDf) broadcast(other) else other, joinOn, "left")
.groupBy("symbol")
.agg(
first(struct(df("*"))) as "hg",
aggFn(struct(gene_set.drop(joinOn: _*)("*"))) as asColumnName,
aggFn(struct(other.drop(joinOn: _*)("*"))) as asColumnName,
)
.select(col("hg.*"), col(asColumnName))
if (aggFirst)
Expand All @@ -102,14 +101,14 @@ object Genes {
max("pLI") as "pli",
max("oe_lof_upper") as "loeuf"
)
df.joinAndMergeWith(gnomadConstraint, Seq("chromosome", "symbol"), "gnomad", aggFirst = true)
df.joinAndMergeWith(gnomadConstraint, Seq("chromosome", "symbol"), "gnomad", aggFirst = true, broadcastOtherDf = true)
}

def withOrphanet(orphanet: DataFrame): DataFrame = {
val orphanetPrepared = orphanet
.select(col("gene_symbol") as "symbol", col("disorder_id"), col("name") as "panel", col("type_of_inheritance") as "inheritance")

df.joinAndMergeWith(orphanetPrepared, Seq("symbol"), "orphanet")
df.joinAndMergeWith(orphanetPrepared, Seq("symbol"), "orphanet", broadcastOtherDf = true)
}

def withOmim(omim: DataFrame): DataFrame = {
Expand All @@ -120,35 +119,37 @@ object Genes {
col("phenotype.omim_id") as "omim_id",
col("phenotype.inheritance") as "inheritance",
col("phenotype.inheritance_code") as "inheritance_code")
df.joinAndMergeWith(omimPrepared, Seq("omim_gene_id"), "omim")
df.joinAndMergeWith(omimPrepared, Seq("omim_gene_id"), "omim", broadcastOtherDf = true)
}

def withDDD(ddd: DataFrame): DataFrame = {
val dddPrepared = ddd.select("disease_name", "symbol")
df.joinAndMergeWith(dddPrepared, Seq("symbol"), "ddd")
df.joinAndMergeWith(dddPrepared, Seq("symbol"), "ddd", broadcastOtherDf = true)
}

def withCosmic(cosmic: DataFrame): DataFrame = {
val cosmicPrepared = cosmic.select("symbol", "tumour_types_germline")
df.joinAndMergeWith(cosmicPrepared, Seq("symbol"), "cosmic")
df.joinAndMergeWith(cosmicPrepared, Seq("symbol"), "cosmic", broadcastOtherDf = true)
}

def withHPO(hpo: DataFrame): DataFrame = {
val hpoPrepared = hpo.select(col("entrez_gene_id"), col("hpo_term_id"), col("hpo_term_name"))
.distinct()
.withColumn("hpo_term_label", concat(col("hpo_term_name"), lit(" ("), col("hpo_term_id"), lit(")")))
df.joinAndMergeWith(hpoPrepared, Seq("entrez_gene_id"), "hpo")
df.joinAndMergeWith(hpoPrepared, Seq("entrez_gene_id"), "hpo", broadcastOtherDf = true)
}

def withSpliceAi(spliceai: DataFrame)(implicit spark: SparkSession): DataFrame = {
import spark.implicits._

val spliceAiPrepared = spliceai
.groupBy("symbol")
.agg(first("max_score") as "max_score")
.select($"symbol", $"max_score.*")
.withColumn("type", when($"ds" === 0, null).otherwise($"type"))

df
.joinAndMergeWith(spliceAiPrepared, Seq("symbol"), "spliceai", aggFirst = true)
.joinAndMergeWith(spliceAiPrepared, Seq("symbol"), "spliceai", aggFirst = true, broadcastOtherDf = true)
.withColumn("spliceai", when($"spliceai.ds".isNull and $"spliceai.type".isNull, null).otherwise($"spliceai"))
}
}
Expand Down
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