mirror of
https://github.com/letic/terraform-provider-google.git
synced 2024-09-06 09:06:44 +00:00
1049 lines
28 KiB
Go
1049 lines
28 KiB
Go
![]() |
package google
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import (
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"fmt"
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"log"
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"time"
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"github.com/hashicorp/terraform/helper/schema"
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"github.com/hashicorp/terraform/helper/validation"
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"google.golang.org/api/dataproc/v1"
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)
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func resourceDataprocJob() *schema.Resource {
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return &schema.Resource{
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Create: resourceDataprocJobCreate,
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Update: resourceDataprocJobUpdate,
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Read: resourceDataprocJobRead,
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Delete: resourceDataprocJobDelete,
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Timeouts: &schema.ResourceTimeout{
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Create: schema.DefaultTimeout(10 * time.Minute),
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Delete: schema.DefaultTimeout(10 * time.Minute),
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},
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Schema: map[string]*schema.Schema{
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"project": {
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Type: schema.TypeString,
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Optional: true,
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ForceNew: true,
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},
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// Ref: https://cloud.google.com/dataproc/docs/reference/rest/v1/projects.regions.jobs#JobReference
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"region": {
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Type: schema.TypeString,
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Optional: true,
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Default: "global",
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ForceNew: true,
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},
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// If a job is still running, trying to delete a job will fail. Setting
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// this flag to true however will force the deletion by first cancelling
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// the job and then deleting it
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"force_delete": {
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Type: schema.TypeBool,
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Default: false,
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Optional: true,
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},
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"reference": {
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Type: schema.TypeList,
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Optional: true,
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Computed: true,
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MaxItems: 1,
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Elem: &schema.Resource{
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Schema: map[string]*schema.Schema{
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"job_id": {
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Type: schema.TypeString,
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Description: "The job ID, which must be unique within the project. The job ID is generated by the server upon job submission or provided by the user as a means to perform retries without creating duplicate jobs",
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Optional: true,
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ForceNew: true,
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Computed: true,
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ValidateFunc: validateRegexp("^[a-zA-Z0-9_-]{1,100}$"),
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},
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},
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},
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},
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"placement": {
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Type: schema.TypeList,
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Required: true,
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MaxItems: 1,
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Elem: &schema.Resource{
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Schema: map[string]*schema.Schema{
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"cluster_name": {
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Type: schema.TypeString,
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Description: "The name of the cluster where the job will be submitted",
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Required: true,
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ForceNew: true,
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},
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"cluster_uuid": {
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Type: schema.TypeString,
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Computed: true,
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Description: "Output-only. A cluster UUID generated by the Cloud Dataproc service when the job is submitted",
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},
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},
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},
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},
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"status": {
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Type: schema.TypeList,
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Computed: true,
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MaxItems: 1,
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Elem: &schema.Resource{
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Schema: map[string]*schema.Schema{
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"state": {
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Type: schema.TypeString,
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Description: "Output-only. A state message specifying the overall job state",
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Computed: true,
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},
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"details": {
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Type: schema.TypeString,
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Description: "Output-only. Optional job state details, such as an error description if the state is ERROR",
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Computed: true,
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},
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"state_start_time": {
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Type: schema.TypeString,
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Description: "Output-only. The time when this state was entered",
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Computed: true,
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},
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"substate": {
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Type: schema.TypeString,
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Description: "Output-only. Additional state information, which includes status reported by the agent",
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Computed: true,
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},
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},
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},
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},
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"driver_output_resource_uri": {
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Type: schema.TypeString,
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Description: "Output-only. A URI pointing to the location of the stdout of the job's driver program",
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Computed: true,
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},
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"driver_controls_files_uri": {
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Type: schema.TypeString,
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Description: "Output-only. If present, the location of miscellaneous control files which may be used as part of job setup and handling. If not present, control files may be placed in the same location as driver_output_uri.",
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Computed: true,
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},
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"labels": {
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Type: schema.TypeMap,
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Description: "Optional. The labels to associate with this job.",
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Optional: true,
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ForceNew: true,
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Elem: &schema.Schema{Type: schema.TypeString},
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},
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"scheduling": {
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Type: schema.TypeList,
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Description: "Optional. Job scheduling configuration.",
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Optional: true,
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ForceNew: true,
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MaxItems: 1,
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Elem: &schema.Resource{
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Schema: map[string]*schema.Schema{
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"max_failures_per_hour": {
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Type: schema.TypeInt,
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Description: "Maximum number of times per hour a driver may be restarted as a result of driver terminating with non-zero code before job is reported failed.",
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Optional: true,
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ForceNew: true,
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ValidateFunc: validation.IntAtMost(10),
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},
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},
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},
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},
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"pyspark_config": pySparkSchema,
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"spark_config": sparkSchema,
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"hadoop_config": hadoopSchema,
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"hive_config": hiveSchema,
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"pig_config": pigSchema,
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"sparksql_config": sparkSqlSchema,
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},
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}
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}
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func resourceDataprocJobUpdate(d *schema.ResourceData, meta interface{}) error {
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// The only updatable value is currently 'force_delete' which is a local
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// only value therefore we don't need to make any GCP calls to update this.
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return resourceDataprocJobRead(d, meta)
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}
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func resourceDataprocJobCreate(d *schema.ResourceData, meta interface{}) error {
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config := meta.(*Config)
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project, err := getProject(d, config)
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if err != nil {
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return err
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}
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jobConfCount := 0
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clusterName := d.Get("placement.0.cluster_name").(string)
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region := d.Get("region").(string)
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submitReq := &dataproc.SubmitJobRequest{
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Job: &dataproc.Job{
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Placement: &dataproc.JobPlacement{
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ClusterName: clusterName,
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},
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Reference: &dataproc.JobReference{
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ProjectId: project,
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},
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},
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}
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if v, ok := d.GetOk("reference.0.job_id"); ok {
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submitReq.Job.Reference.JobId = v.(string)
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}
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if _, ok := d.GetOk("labels"); ok {
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submitReq.Job.Labels = expandLabels(d)
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}
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if v, ok := d.GetOk("pyspark_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.PysparkJob = expandPySparkJob(config)
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}
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if v, ok := d.GetOk("spark_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.SparkJob = expandSparkJob(config)
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}
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if v, ok := d.GetOk("hadoop_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.HadoopJob = expandHadoopJob(config)
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}
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if v, ok := d.GetOk("hive_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.HiveJob = expandHiveJob(config)
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}
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if v, ok := d.GetOk("pig_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.PigJob = expandPigJob(config)
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}
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if v, ok := d.GetOk("sparksql_config"); ok {
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jobConfCount++
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config := extractFirstMapConfig(v.([]interface{}))
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submitReq.Job.SparkSqlJob = expandSparkSqlJob(config)
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}
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if jobConfCount != 1 {
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return fmt.Errorf("You must define and configure exactly one xxx_config block")
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}
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// Submit the job
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job, err := config.clientDataproc.Projects.Regions.Jobs.Submit(
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project, region, submitReq).Do()
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if err != nil {
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return err
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}
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d.SetId(job.Reference.JobId)
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log.Printf("[INFO] Dataproc job %s has been submitted", job.Reference.JobId)
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return resourceDataprocJobRead(d, meta)
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}
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func resourceDataprocJobRead(d *schema.ResourceData, meta interface{}) error {
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config := meta.(*Config)
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region := d.Get("region").(string)
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project, err := getProject(d, config)
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if err != nil {
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return err
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}
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job, err := config.clientDataproc.Projects.Regions.Jobs.Get(
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project, region, d.Id()).Do()
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if err != nil {
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return handleNotFoundError(err, d, fmt.Sprintf("Dataproc Job %q", d.Id()))
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}
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d.Set("force_delete", d.Get("force_delete"))
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d.Set("labels", job.Labels)
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d.Set("driver_output_resource_uri", job.DriverOutputResourceUri)
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d.Set("driver_controls_files_uri", job.DriverControlFilesUri)
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d.Set("placement", flattenJobPlacement(job.Placement))
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d.Set("status", flattenJobStatus(job.Status))
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d.Set("reference", flattenJobReference(job.Reference))
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if job.PysparkJob != nil {
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d.Set("pyspark_config", flattenPySparkJob(job.PysparkJob))
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}
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if job.SparkJob != nil {
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d.Set("spark_config", flattenSparkJob(job.SparkJob))
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}
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if job.HadoopJob != nil {
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d.Set("hadoop_config", flattenHadoopJob(job.HadoopJob))
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}
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if job.HiveJob != nil {
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d.Set("hive_config", flattenHiveJob(job.HiveJob))
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}
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if job.PigJob != nil {
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d.Set("pig_config", flattenPigJob(job.PigJob))
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}
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if job.SparkSqlJob != nil {
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d.Set("sparksql_config", flattenSparkSqlJob(job.SparkSqlJob))
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}
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return nil
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}
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func resourceDataprocJobDelete(d *schema.ResourceData, meta interface{}) error {
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config := meta.(*Config)
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project, err := getProject(d, config)
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if err != nil {
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return err
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}
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region := d.Get("region").(string)
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forceDelete := d.Get("force_delete").(bool)
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timeoutInMinutes := int(d.Timeout(schema.TimeoutDelete).Minutes())
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if forceDelete {
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log.Printf("[DEBUG] Attempting to first cancel Dataproc job %s if it's still running ...", d.Id())
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config.clientDataproc.Projects.Regions.Jobs.Cancel(
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project, region, d.Id(), &dataproc.CancelJobRequest{}).Do()
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// ignore error if we get one - job may be finished already and not need to
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// be cancelled. We do however wait for the state to be one that is
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// at least not active
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waitErr := dataprocJobOperationWait(config, region, project, d.Id(),
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"Cancelling Dataproc job", timeoutInMinutes, 1)
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if waitErr != nil {
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return waitErr
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}
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}
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log.Printf("[DEBUG] Deleting Dataproc job %s", d.Id())
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_, err = config.clientDataproc.Projects.Regions.Jobs.Delete(
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project, region, d.Id()).Do()
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if err != nil {
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return err
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}
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waitErr := dataprocDeleteOperationWait(config, region, project, d.Id(),
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"Deleting Dataproc job", timeoutInMinutes, 1)
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if waitErr != nil {
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return waitErr
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}
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log.Printf("[INFO] Dataproc job %s has been deleted", d.Id())
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d.SetId("")
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return nil
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}
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// ---- PySpark Job ----
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var loggingConfig = &schema.Schema{
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Type: schema.TypeList,
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Description: "The runtime logging config of the job",
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Optional: true,
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Computed: true,
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MaxItems: 1,
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Elem: &schema.Resource{
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Schema: map[string]*schema.Schema{
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"driver_log_levels": {
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Type: schema.TypeMap,
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Description: "Optional. The per-package log levels for the driver. This may include 'root' package name to configure rootLogger. Examples: 'com.google = FATAL', 'root = INFO', 'org.apache = DEBUG'.",
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Optional: true,
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ForceNew: true,
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Elem: &schema.Schema{Type: schema.TypeString},
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},
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},
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},
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}
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|
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var pySparkSchema = &schema.Schema{
|
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Type: schema.TypeList,
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Optional: true,
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ForceNew: true,
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MaxItems: 1,
|
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ConflictsWith: []string{"spark_config", "hadoop_config", "hive_config", "pig_config", "sparksql_config"},
|
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Elem: &schema.Resource{
|
||
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Schema: map[string]*schema.Schema{
|
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"main_python_file_uri": {
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Type: schema.TypeString,
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Description: "Required. The HCFS URI of the main Python file to use as the driver. Must be a .py file",
|
||
|
Required: true,
|
||
|
ForceNew: true,
|
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},
|
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|
|
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"args": {
|
||
|
Type: schema.TypeList,
|
||
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Description: "Optional. The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
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Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
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"python_file_uris": {
|
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Type: schema.TypeList,
|
||
|
Description: "Optional. HCFS file URIs of Python files to pass to the PySpark framework. Supported file types: .py, .egg, and .zip",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
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Elem: &schema.Schema{Type: schema.TypeString},
|
||
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},
|
||
|
|
||
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"jar_file_uris": {
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||
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Type: schema.TypeList,
|
||
|
Description: "Optional. HCFS URIs of jar files to add to the CLASSPATHs of the Python driver and tasks",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
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},
|
||
|
|
||
|
"file_uris": {
|
||
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Type: schema.TypeList,
|
||
|
Description: "Optional. HCFS URIs of files to be copied to the working directory of Python drivers and distributed tasks. Useful for naively parallel tasks",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
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|
},
|
||
|
|
||
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"archive_uris": {
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||
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Type: schema.TypeList,
|
||
|
Description: "Optional. HCFS URIs of archives to be extracted in the working directory of .jar, .tar, .tar.gz, .tgz, and .zip",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Description: "Optional. A mapping of property names to values, used to configure PySpark. Properties that conflict with values set by the Cloud Dataproc API may be overwritten. Can include properties set in /etc/spark/conf/spark-defaults.conf and classes in user code",
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"logging_config": loggingConfig,
|
||
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},
|
||
|
},
|
||
|
}
|
||
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|
||
|
func flattenPySparkJob(job *dataproc.PySparkJob) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"main_python_file_uri": job.MainPythonFileUri,
|
||
|
"args": job.Args,
|
||
|
"python_file_uris": job.PythonFileUris,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
"file_uris": job.FileUris,
|
||
|
"archive_uris": job.ArchiveUris,
|
||
|
"properties": job.Properties,
|
||
|
"logging_config": flattenLoggingConfig(job.LoggingConfig),
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandPySparkJob(config map[string]interface{}) *dataproc.PySparkJob {
|
||
|
job := &dataproc.PySparkJob{}
|
||
|
if v, ok := config["main_python_file_uri"]; ok {
|
||
|
job.MainPythonFileUri = v.(string)
|
||
|
}
|
||
|
if v, ok := config["args"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["python_file_uris"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["file_uris"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["archive_uris"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["logging_config"]; ok {
|
||
|
config := extractFirstMapConfig(v.([]interface{}))
|
||
|
job.LoggingConfig = expandLoggingConfig(config)
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
|
||
|
}
|
||
|
|
||
|
// ---- Spark Job ----
|
||
|
|
||
|
var sparkSchema = &schema.Schema{
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
MaxItems: 1,
|
||
|
ConflictsWith: []string{"pyspark_config", "hadoop_config", "hive_config", "pig_config", "sparksql_config"},
|
||
|
Elem: &schema.Resource{
|
||
|
Schema: map[string]*schema.Schema{
|
||
|
// main driver: can be only one of the class | jar_file
|
||
|
"main_class": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"spark_config.0.main_jar_file_uri"},
|
||
|
},
|
||
|
|
||
|
"main_jar_file_uri": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"spark_config.0.main_class"},
|
||
|
},
|
||
|
|
||
|
"args": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"jar_file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"archive_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"logging_config": loggingConfig,
|
||
|
},
|
||
|
},
|
||
|
}
|
||
|
|
||
|
func flattenSparkJob(job *dataproc.SparkJob) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"main_class": job.MainClass,
|
||
|
"main_jar_file_uri": job.MainJarFileUri,
|
||
|
"args": job.Args,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
"file_uris": job.FileUris,
|
||
|
"archive_uris": job.ArchiveUris,
|
||
|
"properties": job.Properties,
|
||
|
"logging_config": flattenLoggingConfig(job.LoggingConfig),
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandSparkJob(config map[string]interface{}) *dataproc.SparkJob {
|
||
|
job := &dataproc.SparkJob{}
|
||
|
if v, ok := config["main_class"]; ok {
|
||
|
job.MainClass = v.(string)
|
||
|
}
|
||
|
if v, ok := config["main_jar_file_uri"]; ok {
|
||
|
job.MainJarFileUri = v.(string)
|
||
|
}
|
||
|
|
||
|
if v, ok := config["args"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.JarFileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["file_uris"]; ok {
|
||
|
job.FileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["archive_uris"]; ok {
|
||
|
job.ArchiveUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["logging_config"]; ok {
|
||
|
config := extractFirstMapConfig(v.([]interface{}))
|
||
|
job.LoggingConfig = expandLoggingConfig(config)
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
|
||
|
}
|
||
|
|
||
|
// ---- Hadoop Job ----
|
||
|
|
||
|
var hadoopSchema = &schema.Schema{
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
MaxItems: 1,
|
||
|
ConflictsWith: []string{"spark_config", "pyspark_config", "hive_config", "pig_config", "sparksql_config"},
|
||
|
Elem: &schema.Resource{
|
||
|
Schema: map[string]*schema.Schema{
|
||
|
// main driver: can be only one of the main_class | main_jar_file_uri
|
||
|
"main_class": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"hadoop_config.0.main_jar_file_uri"},
|
||
|
},
|
||
|
|
||
|
"main_jar_file_uri": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"hadoop_config.0.main_class"},
|
||
|
},
|
||
|
|
||
|
"args": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"jar_file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"archive_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"logging_config": loggingConfig,
|
||
|
},
|
||
|
},
|
||
|
}
|
||
|
|
||
|
func flattenHadoopJob(job *dataproc.HadoopJob) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"main_class": job.MainClass,
|
||
|
"main_jar_file_uri": job.MainJarFileUri,
|
||
|
"args": job.Args,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
"file_uris": job.FileUris,
|
||
|
"archive_uris": job.ArchiveUris,
|
||
|
"properties": job.Properties,
|
||
|
"logging_config": flattenLoggingConfig(job.LoggingConfig),
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandHadoopJob(config map[string]interface{}) *dataproc.HadoopJob {
|
||
|
job := &dataproc.HadoopJob{}
|
||
|
if v, ok := config["main_class"]; ok {
|
||
|
job.MainClass = v.(string)
|
||
|
}
|
||
|
if v, ok := config["main_jar_file_uri"]; ok {
|
||
|
job.MainJarFileUri = v.(string)
|
||
|
}
|
||
|
|
||
|
if v, ok := config["args"]; ok {
|
||
|
job.Args = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.JarFileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["file_uris"]; ok {
|
||
|
job.FileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["archive_uris"]; ok {
|
||
|
job.ArchiveUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["logging_config"]; ok {
|
||
|
config := extractFirstMapConfig(v.([]interface{}))
|
||
|
job.LoggingConfig = expandLoggingConfig(config)
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
|
||
|
}
|
||
|
|
||
|
// ---- Hive Job ----
|
||
|
|
||
|
var hiveSchema = &schema.Schema{
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
MaxItems: 1,
|
||
|
ConflictsWith: []string{"spark_config", "pyspark_config", "hadoop_config", "pig_config", "sparksql_config"},
|
||
|
Elem: &schema.Resource{
|
||
|
Schema: map[string]*schema.Schema{
|
||
|
// main query: can be only one of query_list | query_file_uri
|
||
|
"query_list": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
ConflictsWith: []string{"hive_config.0.query_file_uri"},
|
||
|
},
|
||
|
|
||
|
"query_file_uri": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"hive_config.0.query_list"},
|
||
|
},
|
||
|
|
||
|
"continue_on_failure": {
|
||
|
Type: schema.TypeBool,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
},
|
||
|
|
||
|
"script_variables": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"jar_file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
},
|
||
|
},
|
||
|
}
|
||
|
|
||
|
func flattenHiveJob(job *dataproc.HiveJob) []map[string]interface{} {
|
||
|
queries := []string{}
|
||
|
if job.QueryList != nil {
|
||
|
queries = job.QueryList.Queries
|
||
|
}
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"query_list": queries,
|
||
|
"query_file_uri": job.QueryFileUri,
|
||
|
"continue_on_failure": job.ContinueOnFailure,
|
||
|
"script_variables": job.ScriptVariables,
|
||
|
"properties": job.Properties,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandHiveJob(config map[string]interface{}) *dataproc.HiveJob {
|
||
|
job := &dataproc.HiveJob{}
|
||
|
if v, ok := config["query_file_uri"]; ok {
|
||
|
job.QueryFileUri = v.(string)
|
||
|
}
|
||
|
if v, ok := config["query_list"]; ok {
|
||
|
job.QueryList = &dataproc.QueryList{
|
||
|
Queries: convertStringArr(v.([]interface{})),
|
||
|
}
|
||
|
}
|
||
|
if v, ok := config["continue_on_failure"]; ok {
|
||
|
job.ContinueOnFailure = v.(bool)
|
||
|
}
|
||
|
if v, ok := config["script_variables"]; ok {
|
||
|
job.ScriptVariables = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.JarFileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
}
|
||
|
|
||
|
// ---- Pig Job ----
|
||
|
|
||
|
var pigSchema = &schema.Schema{
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
MaxItems: 1,
|
||
|
ConflictsWith: []string{"spark_config", "pyspark_config", "hadoop_config", "hive_config", "sparksql_config"},
|
||
|
Elem: &schema.Resource{
|
||
|
Schema: map[string]*schema.Schema{
|
||
|
// main query: can be only one of query_list | query_file_uri
|
||
|
"query_list": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
ConflictsWith: []string{"pig_config.0.query_file_uri"},
|
||
|
},
|
||
|
|
||
|
"query_file_uri": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"pig_config.0.query_list"},
|
||
|
},
|
||
|
|
||
|
"continue_on_failure": {
|
||
|
Type: schema.TypeBool,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
},
|
||
|
|
||
|
"script_variables": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"jar_file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"logging_config": loggingConfig,
|
||
|
},
|
||
|
},
|
||
|
}
|
||
|
|
||
|
func flattenPigJob(job *dataproc.PigJob) []map[string]interface{} {
|
||
|
queries := []string{}
|
||
|
if job.QueryList != nil {
|
||
|
queries = job.QueryList.Queries
|
||
|
}
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"query_list": queries,
|
||
|
"query_file_uri": job.QueryFileUri,
|
||
|
"continue_on_failure": job.ContinueOnFailure,
|
||
|
"script_variables": job.ScriptVariables,
|
||
|
"properties": job.Properties,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandPigJob(config map[string]interface{}) *dataproc.PigJob {
|
||
|
job := &dataproc.PigJob{}
|
||
|
if v, ok := config["query_file_uri"]; ok {
|
||
|
job.QueryFileUri = v.(string)
|
||
|
}
|
||
|
if v, ok := config["query_list"]; ok {
|
||
|
job.QueryList = &dataproc.QueryList{
|
||
|
Queries: convertStringArr(v.([]interface{})),
|
||
|
}
|
||
|
}
|
||
|
if v, ok := config["continue_on_failure"]; ok {
|
||
|
job.ContinueOnFailure = v.(bool)
|
||
|
}
|
||
|
if v, ok := config["script_variables"]; ok {
|
||
|
job.ScriptVariables = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.JarFileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
|
||
|
}
|
||
|
|
||
|
// ---- Spark SQL Job ----
|
||
|
|
||
|
var sparkSqlSchema = &schema.Schema{
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
MaxItems: 1,
|
||
|
ConflictsWith: []string{"spark_config", "pyspark_config", "hadoop_config", "hive_config", "pig_config"},
|
||
|
Elem: &schema.Resource{
|
||
|
Schema: map[string]*schema.Schema{
|
||
|
// main query: can be only one of query_list | query_file_uri
|
||
|
"query_list": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
ConflictsWith: []string{"pig_config.0.query_file_uri"},
|
||
|
},
|
||
|
|
||
|
"query_file_uri": {
|
||
|
Type: schema.TypeString,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
ConflictsWith: []string{"pig_config.0.query_list"},
|
||
|
},
|
||
|
|
||
|
"script_variables": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"properties": {
|
||
|
Type: schema.TypeMap,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"jar_file_uris": {
|
||
|
Type: schema.TypeList,
|
||
|
Optional: true,
|
||
|
ForceNew: true,
|
||
|
Elem: &schema.Schema{Type: schema.TypeString},
|
||
|
},
|
||
|
|
||
|
"logging_config": loggingConfig,
|
||
|
},
|
||
|
},
|
||
|
}
|
||
|
|
||
|
func flattenSparkSqlJob(job *dataproc.SparkSqlJob) []map[string]interface{} {
|
||
|
queries := []string{}
|
||
|
if job.QueryList != nil {
|
||
|
queries = job.QueryList.Queries
|
||
|
}
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"query_list": queries,
|
||
|
"query_file_uri": job.QueryFileUri,
|
||
|
"script_variables": job.ScriptVariables,
|
||
|
"properties": job.Properties,
|
||
|
"jar_file_uris": job.JarFileUris,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func expandSparkSqlJob(config map[string]interface{}) *dataproc.SparkSqlJob {
|
||
|
job := &dataproc.SparkSqlJob{}
|
||
|
if v, ok := config["query_file_uri"]; ok {
|
||
|
job.QueryFileUri = v.(string)
|
||
|
}
|
||
|
if v, ok := config["query_list"]; ok {
|
||
|
job.QueryList = &dataproc.QueryList{
|
||
|
Queries: convertStringArr(v.([]interface{})),
|
||
|
}
|
||
|
}
|
||
|
if v, ok := config["script_variables"]; ok {
|
||
|
job.ScriptVariables = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
if v, ok := config["jar_file_uris"]; ok {
|
||
|
job.JarFileUris = convertStringArr(v.([]interface{}))
|
||
|
}
|
||
|
if v, ok := config["properties"]; ok {
|
||
|
job.Properties = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
|
||
|
return job
|
||
|
|
||
|
}
|
||
|
|
||
|
// ---- Other flatten / expand methods ----
|
||
|
|
||
|
func expandLoggingConfig(config map[string]interface{}) *dataproc.LoggingConfig {
|
||
|
conf := &dataproc.LoggingConfig{}
|
||
|
if v, ok := config["driver_log_levels"]; ok {
|
||
|
conf.DriverLogLevels = convertStringMap(v.(map[string]interface{}))
|
||
|
}
|
||
|
return conf
|
||
|
}
|
||
|
|
||
|
func flattenLoggingConfig(l *dataproc.LoggingConfig) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"driver_log_levels": l.DriverLogLevels,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func flattenJobReference(r *dataproc.JobReference) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"job_id": r.JobId,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func flattenJobStatus(s *dataproc.JobStatus) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"state": s.State,
|
||
|
"details": s.Details,
|
||
|
"state_start_time": s.StateStartTime,
|
||
|
"substate": s.Substate,
|
||
|
},
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func flattenJobPlacement(jp *dataproc.JobPlacement) []map[string]interface{} {
|
||
|
return []map[string]interface{}{
|
||
|
{
|
||
|
"cluster_name": jp.ClusterName,
|
||
|
"cluster_uuid": jp.ClusterUuid,
|
||
|
},
|
||
|
}
|
||
|
}
|