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Merged
merged 9 commits into from
Aug 24, 2023
Merged

SPARKNLP-732 Unify all externally supported file systems and cloud access #13919

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b4f92e1
SPARKNLP-732 Refactoring to unify Cloud access for cache_pretrained p…
danilojsl Apr 17, 2023
66704a3
SPARKNLP-732 Adding support to export NER log file for GCP Storage
danilojsl May 3, 2023
3ef590f
SPARKNLP-732 Refactoring loadSavedModel to import HF models from Clou…
danilojsl May 31, 2023
81fe075
SPARKNLP-732 Adding support for GCP when importing HF models
danilojsl Jun 7, 2023
a5052e1
SPARKNLP-732 Moving Credentials component to aws package
danilojsl Jul 5, 2023
e06e4e0
SPARKNLP-732 Fixing HDFS log and NER Graph load issues
danilojsl Jun 19, 2023
d49314c
SPARKNLP-732 Adding Azure Dependencies
danilojsl Jun 15, 2023
bab8924
SPARKNLP-732 Adding Azure support for all cloud operations
danilojsl Jul 5, 2023
0e6905a
SPARKNLP-732 Adding documentation for Azure, GCP and S3 support
danilojsl Aug 14, 2023
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5 changes: 4 additions & 1 deletion build.sbt
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Original file line number Diff line number Diff line change
Expand Up @@ -151,7 +151,10 @@ lazy val utilDependencies = Seq(
exclude ("com.google.code.findbugs", "annotations")
exclude ("org.slf4j", "slf4j-api"),
gcpStorage,
greex)
greex,
azureIdentity,
azureStorage
)

lazy val typedDependencyParserDependencies = Seq(junit)

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6 changes: 3 additions & 3 deletions docs/api/com/johnsnowlabs/client/CredentialParams.html
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Expand Up @@ -3,9 +3,9 @@
<head>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
<title>Spark NLP 5.0.2 ScalaDoc - com.johnsnowlabs.client.CredentialParams</title>
<meta name="description" content="Spark NLP 5.0.2 ScalaDoc - com.johnsnowlabs.client.CredentialParams" />
<meta name="keywords" content="Spark NLP 5.0.2 ScalaDoc com.johnsnowlabs.client.CredentialParams" />
<title>Spark NLP 5.1.0 ScalaDoc - com.johnsnowlabs.client.aws.CredentialParams</title>
<meta name="description" content="Spark NLP 5.1.0 ScalaDoc - com.johnsnowlabs.client.aws.CredentialParams" />
<meta name="keywords" content="Spark NLP 5.1.0 ScalaDoc com.johnsnowlabs.client.aws.CredentialParams" />
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />


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102 changes: 78 additions & 24 deletions examples/python/training/english/dl-ner/mfa_ner_graphs_s3.ipynb
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Expand Up @@ -8,7 +8,18 @@
"\n",
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp/blob/master/examples/python/training/english/dl-ner/mfa_ner_graphs_s3.ipynb)\n",
"\n",
"# Configuring MFA for S3 access"
"# Training NER with Graphs in S3"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In Spark NLP you can configure the location to store TF Graphs used while training NER models. Starting at Spark NLP 5.1.0, you can set a GCP Storage URI, or Azure Storage URI or DBFS paths like HDFS or Databricks FS.\n",
"\n",
"In this notebook, we are going to see the steps required to use an external S3 URI to store the logs of traning an NER model\n",
"\n",
"To do this, we need to configure the spark session with the required settings for Spark NLP and Spark ML."
]
},
{
Expand Down Expand Up @@ -43,6 +54,68 @@
"print(\"Spark NLP version\", sparknlp.version())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To configure MFA we just need to define the requires values in spark properties as show below. Look an example to get temporal credentials [here](https://github.com/JohnSnowLabs/spark-nlp/blob/master/scripts/aws_tmp_credentials.sh) "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Enter your AWS Access Key:\")\n",
"MY_ACCESS_KEY = input()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Enter your AWS Secret Key:\")\n",
"MY_SECRET_KEY = input()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Enter your AWS Session Key:\")\n",
"MY_SESSION_KEY = input()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Enter your AWS Region:\")\n",
"MY_AWS_REGION"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#S3 Storage configuration\n",
"s3_params = {\n",
" \"spark.jsl.settings.aws.credentials.access_key_id\": MY_ACCESS_KEY,\n",
" \"spark.jsl.settings.aws.credentials.secret_access_key\": MY_SECRET_KEY,\n",
" \"spark.jsl.settings.aws.credentials.session_token\": MY_SESSION_KEY,\n",
" \"spark.jsl.settings.aws.region\": MY_AWS_REGION\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand Down Expand Up @@ -83,27 +156,7 @@
}
],
"source": [
"spark = sparknlp.start()\n",
"spark"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To configure MFA we just need to define the requires values in spark properties as show below. Look an example to get temporal credentials [here](https://github.com/JohnSnowLabs/spark-nlp/blob/master/scripts/aws_tmp_credentials.sh) "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"spark.conf.set(\"spark.jsl.settings.aws.credentials.access_key_id\", \"MY_ACCESS_KEY_ID\")\n",
"spark.conf.set(\"spark.jsl.settings.aws.credentials.secret_access_key\", \"MY_SECRET_ACCESS_KEY_ID\")\n",
"spark.conf.set(\"spark.jsl.settings.aws.credentials.session_token\", \"MY_SESSION_TOKEN\")\n",
"spark.conf.set(\"spark.jsl.settings.aws.region\", \"MY_REGION\")"
"spark = sparknlp.start(params=s3_params)"
]
},
{
Expand Down Expand Up @@ -201,7 +254,7 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -214,7 +267,8 @@
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
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