path: root/python-aws-cdk-aws-kinesisanalytics-flink-alpha.spec

%global _empty_manifest_terminate_build 0
Name:		python-aws-cdk.aws-kinesisanalytics-flink-alpha
Version:	2.83.0a0
Release:	1
Summary:	A CDK Construct Library for Kinesis Analytics Flink applications
License:	Apache-2.0
URL:		https://github.com/aws/aws-cdk
Source0:	https://mirrors.aliyun.com/pypi/web/packages/fa/f4/5098b52d0fdb35daf61d3567b611e0e956a309b05e784e2ea5805f47b12f/aws-cdk.aws-kinesisanalytics-flink-alpha-2.83.0a0.tar.gz
BuildArch:	noarch

Requires:	python3-aws-cdk-lib
Requires:	python3-constructs
Requires:	python3-jsii
Requires:	python3-publication
Requires:	python3-typeguard

%description
<!--END STABILITY BANNER-->
This package provides constructs for creating Kinesis Analytics Flink
applications. To learn more about using using managed Flink applications, see
the [AWS developer
guide](https://docs.aws.amazon.com/kinesisanalytics/latest/java/).
## Creating Flink Applications
To create a new Flink application, use the `Application` construct:
```python
import path as path
import aws_cdk.aws_cloudwatch as cloudwatch
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppTest")
flink_app = flink.Application(stack, "App",
    code=flink.ApplicationCode.from_asset(path.join(__dirname, "code-asset")),
    runtime=flink.Runtime.FLINK_1_11
)
cloudwatch.Alarm(stack, "Alarm",
    metric=flink_app.metric_full_restarts(),
    evaluation_periods=1,
    threshold=3
)
app.synth()
```
The `code` property can use `fromAsset` as shown above to reference a local jar
file in s3 or `fromBucket` to reference a file in s3.
```python
import path as path
import aws_cdk.aws_s3_assets as assets
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppCodeFromBucketTest")
asset = assets.Asset(stack, "CodeAsset",
    path=path.join(__dirname, "code-asset")
)
bucket = asset.bucket
file_key = asset.s3_object_key
flink.Application(stack, "App",
    code=flink.ApplicationCode.from_bucket(bucket, file_key),
    runtime=flink.Runtime.FLINK_1_11
)
app.synth()
```
The `propertyGroups` property provides a way of passing arbitrary runtime
properties to your Flink application. You can use the
aws-kinesisanalytics-runtime library to [retrieve these
properties](https://docs.aws.amazon.com/kinesisanalytics/latest/java/how-properties.html#how-properties-access).
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    property_groups={
        "FlinkApplicationProperties": {
            "input_stream_name": "my-input-kinesis-stream",
            "output_stream_name": "my-output-kinesis-stream"
        }
    },
    # ...
    runtime=flink.Runtime.FLINK_1_15,
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar")
)
```
Flink applications also have specific configuration for passing parameters
when the Flink job starts. These include parameters for checkpointing,
snapshotting, monitoring, and parallelism.
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    checkpointing_enabled=True,  # default is true
    checkpoint_interval=Duration.seconds(30),  # default is 1 minute
    min_pause_between_checkpoints=Duration.seconds(10),  # default is 5 seconds
    log_level=flink.LogLevel.ERROR,  # default is INFO
    metrics_level=flink.MetricsLevel.PARALLELISM,  # default is APPLICATION
    auto_scaling_enabled=False,  # default is true
    parallelism=32,  # default is 1
    parallelism_per_kpu=2,  # default is 1
    snapshots_enabled=False,  # default is true
    log_group=logs.LogGroup(self, "LogGroup")
)
```
Flink applications can optionally be deployed in a VPC:
```python
# bucket: s3.Bucket
# vpc: ec2.Vpc
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    vpc=vpc
)
```

%package -n python3-aws-cdk.aws-kinesisanalytics-flink-alpha
Summary:	A CDK Construct Library for Kinesis Analytics Flink applications
Provides:	python-aws-cdk.aws-kinesisanalytics-flink-alpha
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-aws-cdk.aws-kinesisanalytics-flink-alpha
<!--END STABILITY BANNER-->
This package provides constructs for creating Kinesis Analytics Flink
applications. To learn more about using using managed Flink applications, see
the [AWS developer
guide](https://docs.aws.amazon.com/kinesisanalytics/latest/java/).
## Creating Flink Applications
To create a new Flink application, use the `Application` construct:
```python
import path as path
import aws_cdk.aws_cloudwatch as cloudwatch
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppTest")
flink_app = flink.Application(stack, "App",
    code=flink.ApplicationCode.from_asset(path.join(__dirname, "code-asset")),
    runtime=flink.Runtime.FLINK_1_11
)
cloudwatch.Alarm(stack, "Alarm",
    metric=flink_app.metric_full_restarts(),
    evaluation_periods=1,
    threshold=3
)
app.synth()
```
The `code` property can use `fromAsset` as shown above to reference a local jar
file in s3 or `fromBucket` to reference a file in s3.
```python
import path as path
import aws_cdk.aws_s3_assets as assets
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppCodeFromBucketTest")
asset = assets.Asset(stack, "CodeAsset",
    path=path.join(__dirname, "code-asset")
)
bucket = asset.bucket
file_key = asset.s3_object_key
flink.Application(stack, "App",
    code=flink.ApplicationCode.from_bucket(bucket, file_key),
    runtime=flink.Runtime.FLINK_1_11
)
app.synth()
```
The `propertyGroups` property provides a way of passing arbitrary runtime
properties to your Flink application. You can use the
aws-kinesisanalytics-runtime library to [retrieve these
properties](https://docs.aws.amazon.com/kinesisanalytics/latest/java/how-properties.html#how-properties-access).
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    property_groups={
        "FlinkApplicationProperties": {
            "input_stream_name": "my-input-kinesis-stream",
            "output_stream_name": "my-output-kinesis-stream"
        }
    },
    # ...
    runtime=flink.Runtime.FLINK_1_15,
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar")
)
```
Flink applications also have specific configuration for passing parameters
when the Flink job starts. These include parameters for checkpointing,
snapshotting, monitoring, and parallelism.
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    checkpointing_enabled=True,  # default is true
    checkpoint_interval=Duration.seconds(30),  # default is 1 minute
    min_pause_between_checkpoints=Duration.seconds(10),  # default is 5 seconds
    log_level=flink.LogLevel.ERROR,  # default is INFO
    metrics_level=flink.MetricsLevel.PARALLELISM,  # default is APPLICATION
    auto_scaling_enabled=False,  # default is true
    parallelism=32,  # default is 1
    parallelism_per_kpu=2,  # default is 1
    snapshots_enabled=False,  # default is true
    log_group=logs.LogGroup(self, "LogGroup")
)
```
Flink applications can optionally be deployed in a VPC:
```python
# bucket: s3.Bucket
# vpc: ec2.Vpc
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    vpc=vpc
)
```

%package help
Summary:	Development documents and examples for aws-cdk.aws-kinesisanalytics-flink-alpha
Provides:	python3-aws-cdk.aws-kinesisanalytics-flink-alpha-doc
%description help
<!--END STABILITY BANNER-->
This package provides constructs for creating Kinesis Analytics Flink
applications. To learn more about using using managed Flink applications, see
the [AWS developer
guide](https://docs.aws.amazon.com/kinesisanalytics/latest/java/).
## Creating Flink Applications
To create a new Flink application, use the `Application` construct:
```python
import path as path
import aws_cdk.aws_cloudwatch as cloudwatch
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppTest")
flink_app = flink.Application(stack, "App",
    code=flink.ApplicationCode.from_asset(path.join(__dirname, "code-asset")),
    runtime=flink.Runtime.FLINK_1_11
)
cloudwatch.Alarm(stack, "Alarm",
    metric=flink_app.metric_full_restarts(),
    evaluation_periods=1,
    threshold=3
)
app.synth()
```
The `code` property can use `fromAsset` as shown above to reference a local jar
file in s3 or `fromBucket` to reference a file in s3.
```python
import path as path
import aws_cdk.aws_s3_assets as assets
import aws_cdk as core
import aws_cdk.aws_kinesisanalytics_flink_alpha as flink
app = core.App()
stack = core.Stack(app, "FlinkAppCodeFromBucketTest")
asset = assets.Asset(stack, "CodeAsset",
    path=path.join(__dirname, "code-asset")
)
bucket = asset.bucket
file_key = asset.s3_object_key
flink.Application(stack, "App",
    code=flink.ApplicationCode.from_bucket(bucket, file_key),
    runtime=flink.Runtime.FLINK_1_11
)
app.synth()
```
The `propertyGroups` property provides a way of passing arbitrary runtime
properties to your Flink application. You can use the
aws-kinesisanalytics-runtime library to [retrieve these
properties](https://docs.aws.amazon.com/kinesisanalytics/latest/java/how-properties.html#how-properties-access).
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    property_groups={
        "FlinkApplicationProperties": {
            "input_stream_name": "my-input-kinesis-stream",
            "output_stream_name": "my-output-kinesis-stream"
        }
    },
    # ...
    runtime=flink.Runtime.FLINK_1_15,
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar")
)
```
Flink applications also have specific configuration for passing parameters
when the Flink job starts. These include parameters for checkpointing,
snapshotting, monitoring, and parallelism.
```python
# bucket: s3.Bucket
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    checkpointing_enabled=True,  # default is true
    checkpoint_interval=Duration.seconds(30),  # default is 1 minute
    min_pause_between_checkpoints=Duration.seconds(10),  # default is 5 seconds
    log_level=flink.LogLevel.ERROR,  # default is INFO
    metrics_level=flink.MetricsLevel.PARALLELISM,  # default is APPLICATION
    auto_scaling_enabled=False,  # default is true
    parallelism=32,  # default is 1
    parallelism_per_kpu=2,  # default is 1
    snapshots_enabled=False,  # default is true
    log_group=logs.LogGroup(self, "LogGroup")
)
```
Flink applications can optionally be deployed in a VPC:
```python
# bucket: s3.Bucket
# vpc: ec2.Vpc
flink_app = flink.Application(self, "Application",
    code=flink.ApplicationCode.from_bucket(bucket, "my-app.jar"),
    runtime=flink.Runtime.FLINK_1_15,
    vpc=vpc
)
```

%prep
%autosetup -n aws-cdk.aws-kinesisanalytics-flink-alpha-2.83.0a0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-aws-cdk.aws-kinesisanalytics-flink-alpha -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 2.83.0a0-1
- Package Spec generated